Lars Kai Hansen

发表

Dynamic components of linear stable mixtures from fractional low order moments

Thomas Fabricius, Preben Kidmose, Lars Kai Hansen, 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

Approaches To Better Context Modeling And Categorization

Lars Kai Hansen, R. E. Madsen, Jan Larsen, 2005 .

Nonlinear versus Linear Models in Functional Neuroimaging: Learning Curves and Generalization Crossover

Lars Kai Hansen, Olaf B. Paulson, Niels J. S. Mørch, 1997, IPMI.

Decomposing the time-frequency representation of EEG using non-negative matrix and multi-way factorization

Lars Kai Hansen, Morten Mørup, Josef Parnas, 2006 .

The Center for Integrated Molecular Brain Imaging (Cimbi) database

Hartwig R. Siebner, Lars Kai Hansen, Olaf B. Paulson, 2016, NeuroImage.

On the Robustness of Maximum Entropy Relationships for Complexity Distributions of Nucleotide Sequences

Lars Kai Hansen, Peter Salamon, John C. Wootton, 1993, Comput. Chem..

Bayesian Non-negative Matrix Factorization

Ole Winther, Lars Kai Hansen, Mikkel N. Schmidt, 2009, ICA.

Tuning pruning in sparse non-negative matrix factorization

Lars Kai Hansen, Morten Mørup, 2009, 2009 17th European Signal Processing Conference.

Modeling latency and shape changes in trial based neuroimaging data

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2011, 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

NMF on Positron Emission Tomography

Lars Kai Hansen, Claus Svarer, Gitte Moos Knudsen, 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

Aggregating explainability methods for neural networks stabilizes explanations pdf

Lars Kai Hansen, Laura Rieger, 2019, ArXiv.

Model sparsity and brain pattern interpretation of classification models in neuroimaging

Lars Kai Hansen, Stephen C. Strother, Kristoffer Hougaard Madsen, 2012, Pattern Recognit..

Meta-analytic clustering of molecular neuroimaging studies

Lars Kai Hansen, Claus Svarer, Finn Årup Nielsen, 2004 .

Infinite Relational Modeling of Functional Connectivity in Resting State fMRI

Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup, 2010, NIPS.

Temporal Feature Integration for Music Organisation

Lars Kai Hansen, Jan Larsen, Anders Meng, 2006 .

Detection of Skin Cancer by Classification of

Lars Kai Hansen, Jan Larsen, Sigurdur Sigurdsson, 2004 .

Pitch Based Sound Classification

Lars Kai Hansen, Andreas Brinch Nielsen, Ulrik Kjems, 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

Temporal Feature Integration for Music Genre Classification

Lars Kai Hansen, Jan Larsen, Peter Ahrendt, 2007, IEEE Transactions on Audio, Speech, and Language Processing.

Pruning the vocabulary for better context recognition

Lars Kai Hansen, Jan Larsen, Rasmus Elsborg Madsen, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

Visualization of Nonlinear Classification Models in Neuroimaging - Signed Sensitivity Maps

Lars Kai Hansen, Stephen C. Strother, Kristoffer Hougaard Madsen, 2012, BIOSIGNALS.

EEG source reconstruction performance as a function of skull conductance contrast

Lars Kai Hansen, Sofie Therese Hansen, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Is Cognitive Activity of Speech Based On Statistical Independence

Lars Kai Hansen, Ling Feng, 2008 .

Effect of Spatial Alignment Transformations in PCA and ICA of Functional Neuroimages

Yongyi Yang, Lars Kai Hansen, Stephen C. Strother, 2007, IEEE Transactions on Medical Imaging.

Multiview Bayesian Correlated Component Analysis

Lars Kai Hansen, Simon Kamronn, Andreas Trier Poulsen, 2015, Neural Computation.

EEG source reconstruction using sparse basis function representations

Lars Kai Hansen, Sofie Therese Hansen, L. K. Hansen, 2014, 2014 International Workshop on Pattern Recognition in Neuroimaging.

Mining the posterior cingulate: Segregation between memory and pain components

Lars Kai Hansen, Finn Årup Nielsen, Daniela Balslev, 2005, NeuroImage.

Blind Separation of More Sources than Sensors in Convolutive Mixtures

Lars Kai Hansen, Rasmus Kongsgaard Olsson, L. K. Hansen, 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

Multiuser detection and channel estimation: Exact and approximate methods

Thomas Fabricius, Lars Kai Hansen, Carl Edward Rasmussen, 2003 .

The Quantitative Evaluation of Functional Neuroimaging Experiments: The NPAIRS Data Analysis Framework

Lars Kai Hansen, Jon Anderson, Stephen C. Strother, 2000, NeuroImage.

Structuring Neural Networks for More Explainable Predictions

Klaus-Robert Müller, Lars Kai Hansen, Grégoire Montavon, 2018 .

The Smartphone Brain Scanner: A Mobile Real-time Neuroimaging System pdf

Lars Kai Hansen, Arkadiusz Stopczynski, Jakob Eg Larsen, 2013, ArXiv.

Semi-blind source separation using head-related transfer functions [speech signal separation]

Lars Kai Hansen, Michael Syskind Pedersen, Karsten Boye Rasmussen, 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Cognitive Component Analysis

Lars Kai Hansen, Ling Feng, Ling Feng, 2008 .

Measuring engagement in a classroom: Synchronised neural recordings during a video presentation pdf

Lucas C. Parra, Jacek Dmochowski, Lars Kai Hansen, 2016, ArXiv.

Approximate L0 constrained non-negative matrix and tensor factorization

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2008, 2008 IEEE International Symposium on Circuits and Systems.

Demonstration: A smartphone 3D functional brain scanner

Lars Kai Hansen, Arkadiusz Stopczynski, Jakob Eg Larsen, 2011, NIPS 2011.

Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm

Ole Winther, Lars Kai Hansen, Jens Nielsen, 2006, Bioinform..

System Identification with Neural Networks

Niels Kjølstad Poulsen, Lars Kai Hansen, Ole Ravn, 2000 .

Smartphones Get Emotional: Mind Reading Images and Reconstructing the Neural Sources

Lars Kai Hansen, Arkadiusz Stopczynski, Jakob Eg Larsen, 2011, ACII.

Evaluating Models of Dynamic Functional Connectivity Using Predictive Classification Accuracy

Vince D. Calhoun, Lars Kai Hansen, Morten Mørup, 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Functional Volumes Modeling using Kernel Density Estimation

Lars Kai Hansen, Finn Aarup Nielsen, 2000 .

Discrimination of cylinders with different wall thicknesses using neural networks and simulated dolphin sonar signals

Lars Kai Hansen, Jan Larsen, L. N. Andersen, 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).

Modeling text with generalizable Gaussian mixtures

Lars Kai Hansen, Jan Larsen, Finn Årup Nielsen, 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

On the time required for identification of visual objects

Lars Kai Hansen, Anders Petersen, Søren Kyllingsbæk, 2010 .

A simple defense against adversarial attacks on heatmap explanations pdf

Lars Kai Hansen, Laura Rieger, L. K. Hansen, 2020, ArXiv.

Hierarchical Bayesian model for simultaneous EEG source and forward model reconstruction (SOFOMORE)

Ole Winther, Lars Kai Hansen, Carsten Stahlhut, 2009, 2009 IEEE International Workshop on Machine Learning for Signal Processing.

Automatic Segmentation of Age-related White-Matter Changes in a multi-centre study

Lars Kai Hansen, Egill Rostrup, F. Barkhof, 2006 .

Probabilistic Hierarchical Clustering with Labeled and Unlabeled Data

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 2001 .

Shifted Independent Component Analysis

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2007, ICA.

An ICA algorithm for analyzing multiple data sets

Lars Kai Hansen, Stephen C. Strother, Miles N. Wernick, 2002, Proceedings. International Conference on Image Processing.

EEG in the classroom: Synchronised neural recordings during video presentation

Lucas C. Parra, Lars Kai Hansen, Simon Kamronn, 2016, Scientific Reports.

Archetypal analysis for machine learning

Lars Kai Hansen, Morten Mørup, L. K. Hansen, 2010, 2010 IEEE International Workshop on Machine Learning for Signal Processing.

Motion correction of single‐voxel spectroscopy by independent component analysis applied to spectra from nonanesthetized pediatric subjects

Lars Kai Hansen, Robin de Nijs, Maria J Miranda, 2009, Magnetic resonance in medicine.

Single-Trial Decoding of Scalp EEG under Natural Conditions

Nicolai Pedersen, Lars Kai Hansen, Sofie Therese Hansen, 2019, Comput. Intell. Neurosci..

Frontal alpha oscillations distinguish leaders from followers: Multivariate decoding of mutually interacting brains

Lars Kai Hansen, Christopher D. Frith, Andreas Roepstorff, 2014, NeuroImage.

Kernel Methods for Machine Learning with Life Science Applications

Ole Winther, Lars Kai Hansen, L. K. Hansen, 2013 .

Semi-Supervised Kernel PCA pdf

Lars Kai Hansen, Christian Walder, Ricardo Henao, 2010, ArXiv.

Towards a universal representation for audio information retrieval and analysis

Lars Kai Hansen, Jan Larsen, Bjørn Sand Jensen, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Creating Semantic Representations

Lars Kai Hansen, Finn Årup Nielsen, F. Nielsen, 2020, Statistical Semantics.

Modeling media as latent semantics based on cognitive components

Lars Kai Hansen, Michael Kai Petersen, L. K. Hansen, 2010 .

Top-down attentionwith features missing at random

Lars Kai Hansen, Jan Larsen, Letizia Marchegiani, 2011, 2011 IEEE International Workshop on Machine Learning for Signal Processing.

Optimized combination, regularization, and pruning in parallel consensual neural networks

Johannes R. Sveinsson, Jon Atli Benediktsson, Lars Kai Hansen, 1998, Remote Sensing.

Expansion of the Variational Garrote to a Multiple Measurement Vectors Model

Lars Kai Hansen, Sofie Therese Hansen, Carsten Stahlhut, 2013, SCAI.

Regularization of Neural Networks

Lars Kai Hansen, Jan Larsen, Claus Svarer, 1996 .

Decoding Complex Cognitive States Online by Manifold Regularization in Real-Time fMRI

Lars Kai Hansen, Kristoffer Hougaard Madsen, L. K. Hansen, 2011, MLINI.

Cogito Componentiter Ergo Sum

Lars Kai Hansen, Ling Feng, 2006, ICA.

HIERARCHICALBAYESIANMODEL FOR SIMULTANEOUSEEG SOURCE AND FORWARDMODEL RECONSTRUCTION(SOFOMORE)

Lars Kai Hansen, Carsten Stahlhut, Morten Merup, 2009 .

Semantic Approaches for Knowledge Discovery and Retrieval in Biomedicine

Lars Kai Hansen, Bartlomiej Wilkowski, L. K. Hansen, 2011 .

Unsupervised speaker change detection for broadcast news segmentation

Lars Kai Hansen, Lasse Lohilahti Mølgaard, Kasper Winther Jørgensen, 2006, 2006 14th European Signal Processing Conference.

Stochastic linear learning: Exact test and training error averages

Lars Kai Hansen, L. K. Hansen, 1993, Neural Networks.

Pruning the vocabulary for better context recognition

Lars Kai Hansen, R. E. Madsen, Jan Larsen, 2004, ICPR 2004.

A Multivariate Approach to Functional Neuro Modeling

Lars Kai Hansen, L. K. Hansen, Niels Mørch, 1998 .

Independent component analysis for understanding multimedia content

Ole Winther, Lars Kai Hansen, Jan Larsen, 2002, Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing.

Identification of non-linear models of neural activity in BOLD fMRI

Lars Kai Hansen, Kristoffer Hougaard Madsen, Daniel J. Jacobsen, 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

Phase transition in PCA with missing data: Reduced signal-to-noise ratio, not sample size! pdf

Lars Kai Hansen, L. K. Hansen, Niels Bruun Ipsen, 2019, ICML.

Heuristics for speeding up gaze estimation

Lars Kai Hansen, Martin Vester-Christensen, Bjarne Kjær Ersbøll, 2005 .

Towards semen quality assessment using neural networks

Lars Kai Hansen, Peter Salamon, C. Linneberg, 1994, Proceedings of IEEE Workshop on Neural Networks for Signal Processing.

Sequence Classification Using Third-Order Moments

Lars Kai Hansen, L. K. Hansen, Rasmus Troelsgård, 2018, Neural Computation.

Modelling the Haemodynamic Response in fMRI with Smooth FIR Filters

Lars Kai Hansen, Finn Årup Nielsen, Cyril Goutte, 2000, IEEE Trans. Medical Imaging.

A Genre Classification Plug-in for Data Collection

Kaare Brandt Petersen, Lars Kai Hansen, Jerónimo Arenas-García, 2006, ISMIR.

BredeQuery: Coordinate-Based Meta-analytic Search of Neuroscientific Literature from the SPM Environment

Lars Kai Hansen, Finn Årup Nielsen, Bartlomiej Wilkowski, 2009, BIOSTEC.

Exploring fMRI data for periodic signal components

Lars Kai Hansen, Jan Larsen, Finn Årup Nielsen, 2002, Artif. Intell. Medicine.

The Smartphone Brain Scanner: A Portable Real-Time Neuroimaging System

Lars Kai Hansen, Arkadiusz Stopczynski, Jakob Eg Larsen, 2013, PloS one.

A Probabilistic Neural Network Framework for the Detection of Malignant Melanoma

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 2001 .

Convolutive ICA (c-ICA) captures complex spatio-temporal EEG activity

Lars Kai Hansen, Lars Arendt-Nielsen, Andrew C. N. Chen, 2004 .

A New Database for Speaker Recognition

Lars Kai Hansen, Ling Feng, 2005 .

Linear State-Space Models for Blind Source Separation

Lars Kai Hansen, Rasmus Kongsgaard Olsson, L. K. Hansen, 2006, J. Mach. Learn. Res..

Nonlinear denoising and analysis of neuroimages with kernel principal component analysis and pre-image estimation

Lars Kai Hansen, Kristoffer Hougaard Madsen, Peter Mondrup Rasmussen, 2012, NeuroImage.

Denoising by semi-supervised kernel PCA preimaging

Lars Kai Hansen, L. K. Hansen, Trine Julie Abrahamsen, 2014, Pattern Recognit. Lett..

Adaptive Regularization in Neural Network Modeling

Lars Kai Hansen, Jan Larsen, Claus Svarer, 1996, Neural Networks: Tricks of the Trade.

Biomedical Engineering at the Technical University of Denmark

Lars Kai Hansen, Jens E. Wilhjelm, Jørgen Arendt Jensen, 1998 .

Learning the solution sparsity of an ill-posed linear inverse problem with the Variational Garrote

Lars Kai Hansen, Sofie Therese Hansen, Michael Riis Andersen, 2013, 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

Model Selection for Convolutive ICA with an Application to Spatiotemporal Analysis of EEG

Lars Kai Hansen, Scott Makeig, Mads Dyrholm, 2007, Neural Computation.

Attention: A machine learning perspective

Lars Kai Hansen, L. K. Hansen, 2012, 2012 3rd International Workshop on Cognitive Information Processing (CIP).

Bayesian Structure Learning for Dynamic Brain Connectivity

Ole Winther, Oluwasanmi Koyejo, Lars Kai Hansen, 2018, AISTATS.

Pruning with generalization based weight saliencies: gamma-OBD, gamma-OBS

Lars Kai Hansen, Jan Larsen, Morten With Pedersen, 1995, NIPS.

Sparse Spatio-temporal Inference of Electromagnetic Brain Sources

Lars Kai Hansen, David P. Wipf, Hagai Attias, 2010, MLMI.

A Differential Privacy Workflow for Inference of Parameters in the Rasch Model

Lars Kai Hansen, Teresa Anna Steiner, David Enslev Nyrnberg, 2018, MIDAS/PAP@PKDD/ECML.

Inferring Visual Semantic Similarity with Deep Learning and Wikidata: Introducing imagesim-353*

Lars Kai Hansen, Finn Årup Nielsen, 2018, DL4KGS@ESWC.

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning

Wojciech Samek, Lars Kai Hansen, Andrea Vedaldi, 2019, Explainable AI.

Mean field reconstruction with snaky edge hints

Lars Kai Hansen, Peter Alshede Philipsen, Peter Aundal Toft, 1996 .

Discussion of a Paper by Lange and Zeger

Lars Kai Hansen, 1997 .

Imputating missing values in diary records of sun-exposure study

Lars Kai Hansen, Hans Christian Wulf, Jan Larsen, 2001, Neural Networks for Signal Processing XI: Proceedings of the 2001 IEEE Signal Processing Society Workshop (IEEE Cat. No.01TH8584).

Quantitative analysis of ultrasound B-mode images of carotid atherosclerotic plaque: correlation with visual classification and histological examination

Lars Kai Hansen, Jens E. Wilhjelm, S. K. Jespersen, 1998, IEEE Transactions on Medical Imaging.

Guest Editorial: Special Issue on Statistics of Shapes and Textures

Lars Kai Hansen, Jon Sporring, Mads Nielsen, 2004, Journal of Mathematical Imaging and Vision.

SOFOMORE: Combined EEG source and forward model reconstruction

Ole Winther, Lars Kai Hansen, Morten Mørup, 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Mean Field Reconstruction with Snaky Edge Hints: INVERSE METHODS - Interdisciplinary elements of Methodology, Computation and Application

Lars Kai Hansen, Peter A. Philipsen, Peter Aundal Toft, 1996 .

On Affine Non-Negative Matrix Factorization

Lars Kai Hansen, L. K. Hansen, Hans Laurberg, 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

Regularization with a Pruning Prior

Lars Kai Hansen, Cyril Goutte, L. K. Hansen, 1997, Neural Networks.

A Hold-out method to correct PCA variance inflation

Lars Kai Hansen, Antonio Artés-Rodríguez, L. K. Hansen, 2012, 2012 3rd International Workshop on Cognitive Information Processing (CIP).

Design of robust neural network classifiers

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

Good Friends, Bad News - Affect and Virality in Twitter pdf

Lars Kai Hansen, Finn Årup Nielsen, Michael Etter, 2011, ArXiv.

Restoring the Generalizability of SVM Based Decoding in High Dimensional Neuroimage Data

Lars Kai Hansen, L. K. Hansen, Trine Julie Abrahamsen, 2011, MLINI.

Modelling dense relational data

Lars Kai Hansen, Morten Mørup, Mikkel N. Schmidt, 2012, 2012 IEEE International Workshop on Machine Learning for Signal Processing.

How Many Separable Sources? Model Selection In Independent Components Analysis

Lars Kai Hansen, Roger P. Woods, L. K. Hansen, 2015, PloS one.

Neural classifier construction using regularization, pruning and test error estimation

Lars Kai Hansen, Jan Larsen, Michael Larsen, 1998, Neural Networks.

Theorems on Positive Data: On the Uniqueness of NMF

Mark D. Plumbley, Lars Kai Hansen, Søren Holdt Jensen, 2008, Comput. Intell. Neurosci..

Structure Learning in Audio

Lars Kai Hansen, Andreas Brinch Nielsen, L. K. Hansen, 2009 .

A Harmonic Excitation State-Space Approach to Blind Separation of Speech

Lars Kai Hansen, Rasmus Kongsgaard Olsson, 2004, NIPS.

2011 Ieee International Workshop on Machine Learning for Signal Processing a Randomized Heuristic for Kernel Parameter Selection with Large-scale Multi-class Data

Lars Kai Hansen, L. K. Hansen, Trine Julie Abrahamsen, 2022 .

Are all e-customers alike?

Lars Kai Hansen, Jan Larsen, Jens Hørlück, 2001 .

Book Review: "Time Series Prediction: Forecasting the Future and Understanding the Past", Eds. Andreas S. Weigend and Neil A. Gershenfeld

Lars Kai Hansen, 1994, Int. J. Neural Syst..

Interactive information visualization in neuroimaging

Lars Kai Hansen, Finn Årup Nielsen, L. K. Hansen, 1997, NPIV '97.

Microstate EEGlab toolbox: An introductory guide

Lars Kai Hansen, Nicolas Langer, Andreas Trier Poulsen, 2018, bioRxiv.

Model Order Estimation for Independent Component Analysis of Epoched EEG Signals

Lars Kai Hansen, Morten Mørup, Peter Mondrup Rasmussen, 2008, BIOSIGNALS.

Segmentation of age-related white matter changes in a clinical multi-center study

Lars Kai Hansen, Egill Rostrup, Olaf B. Paulson, 2008, NeuroImage.

MIRANDA - Music Information Retrieval And Data Acquisition

Kaare Brandt Petersen, Lars Kai Hansen, Tue Lehn-Schiøler, 2006 .

Identification of Functional Clusters in the Striatum Using Infinite Relational Modeling

Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup, 2011, MLINI.

Optimal filtering of dynamics in short-time features for music organization

Lars Kai Hansen, Jan Larsen, Jerónimo Arenas-García, 2006, ISMIR.

On Low-level Cognitive Components of Speech

Lars Kai Hansen, Ling Feng, Ling Feng, 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

Active Learning Solution on Distributed Edge Computing pdf

Lars Kai Hansen, Jia Qian, Sayantan Sengupta, 2019, ArXiv.

Mathematical modeling and visualization of functional neuroimages

Lars Kai Hansen, Kristoffer Hougaard Madsen, Peter Mondrup Rasmussen, 2011 .

Structure learning by pruning in independent component analysis

Lars Kai Hansen, Andreas Brinch Nielsen, L. K. Hansen, 2008, Neurocomputing.

Explainable ai – preface

Wojciech Samek, Lars Kai Hansen, Andrea Vedaldi, 2019 .

On the Relevance of Spectral Features for Instrument Classification

Lars Kai Hansen, Jerónimo Arenas-García, Andreas Brinch Nielsen, 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

Probabilistic Decoupling of Labels in Classification pdf

Lars Kai Hansen, L. K. Hansen, Jeppe Nørregaard, 2019, ArXiv.

Open semantic analysis: The case of word level semantics in Danish

Lars Kai Hansen, Finn Årup Nielsen, 2017 .

Deformable Models for Eye Tracking

Lars Kai Hansen, Martin Vester-Christensen, Bjarne Kjær Ersbøll, 2005 .

ICA of functional MRI data: an overview.

Vince D. Calhoun, Lars Kai Hansen, Jan Larsen, 2003 .

Linear unlearning for cross-validation

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 1996, Adv. Comput. Math..

The Complexity of Social Media Response: Statistical Evidence For One-Dimensional Engagement Signal in Twitter pdf

Lars Kai Hansen, Damian Konrad Kowalczyk, 2020, ICAART.

Multimodal Data Fusion [Scanning the Issue]

Lars Kai Hansen, Christian Jutten, Tülay Adali, 2015, Proc. IEEE.

Functional Brain Imaging by EEG: A Window to the Human Mind

Ole Winther, Lars Kai Hansen, Carsten Stahlhut, 2012 .

EEG source imaging assists decoding in a face recognition task

Nicolai Pedersen, Lars Kai Hansen, Sofie Therese Hansen, 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Optimization of recurrent neural networks for time series modeling

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 1997 .

Boltzmann learning of parameters in cellular neural networks

Lars Kai Hansen, 1992, CNNA '92 Proceedings Second International Workshop on Cellular Neural Networks and Their Applications.

A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis

Lars Kai Hansen, L. K. Hansen, Trine Julie Abrahamsen, 2011, J. Mach. Learn. Res..

Enhanced Context Recognition by Sensitivity Pruned Vocabularies

Lars Kai Hansen, R. E. Madsen, Sigurdur Sigurdsson, 2004 .

Distributed Active Learning Strategies on Edge Computing

Lars Kai Hansen, Jia Qian, Sarada Prasad Gochhayat, 2019, 2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom).

Unmixing Oscillatory Brain Activity by EEG Source Localization and Empirical Mode Decomposition

Hartwig R. Siebner, Lars Kai Hansen, Danilo P. Mandic, 2019, Comput. Intell. Neurosci..

Training and evaluation of neural networks for multi-variate time series processing

Lars Kai Hansen, Jan Larsen, Torben L. Fog, 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

Emotional nodes among lines of lyrics

Lars Kai Hansen, Michael Kai Petersen, 2011, Face and Gesture 2011.

Modeling of activation data in the BrainMap™ database: Detection of outliers

Lars Kai Hansen, Finn Arup Nielsen, F. Nielsen, 2002, Human brain mapping.

A Topic Model Approach to Multi-Modal Similarity pdf

Lars Kai Hansen, Bjørn Sand Jensen, Rasmus Troelsgård, 2014, ArXiv.

Latent semantics as cognitive components

Lars Kai Hansen, Morten Mørup, Michael Kai Petersen, 2010, 2010 2nd International Workshop on Cognitive Information Processing.

Independent Component Analysis in a convoluted world

Lars Kai Hansen, Mads Dyrholm, L. K. Hansen, 2006 .

Castsearch - Context Based Spoken Document Retrieval

Lars Kai Hansen, Lasse Lohilahti Mølgaard, Kasper Winther Jørgensen, 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

Predictability of mobile phone associations

Lars Kai Hansen, Jan Larsen, Bjørn Sand Jensen, 2010 .

Latent Space Oddity: on the Curvature of Deep Generative Models

Lars Kai Hansen, Søren Hauberg, Georgios Arvanitidis, 2017, ICLR.

Towards Cognitive Component Analysis

Lars Kai Hansen, Jan Larsen, Peter Ahrendt, 2005 .

Phonemes as Short Time Cognitive Components

Lars Kai Hansen, Ling Feng, Ling Feng, 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

Mean-Field Approaches to Independent Component Analysis

Ole Winther, Lars Kai Hansen, Pedro A. d. F. R. Højen-Sørensen, 2002, Neural Computation.

Estimating the Number of Sources in a Noisy Convolutive Mixture Using BIC

Lars Kai Hansen, Rasmus Kongsgaard Olsson, 2004, ICA.

Maximum Likelihood Estimation of Riemannian Metrics from Euclidean Data

Lars Kai Hansen, Søren Hauberg, Georgios Arvanitidis, 2017, GSI.

Music Genre Classification Systems - A Computational Approach

Lars Kai Hansen, L. K. Hansen, Peter Ahrendt, 2006 .

Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

Lars Kai Hansen, Allan Aasbjerg Nielsen, Rashpal S. Gill, 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

An evaluation of EEG scanner's dependence on the imaging technique, forward model computation method, and array dimensionality

Lars Kai Hansen, Arkadiusz Stopczynski, Hagai Attias, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

A Cross-Platform Smartphone Brain Scanner

Lars Kai Hansen, Arkadiusz Stopczynski, Jakob Eg Larsen, 2012 .

Infinite multiple membership relational modeling for complex networks

Lars Kai Hansen, Morten Mørup, Mikkel N. Schmidt, 2011, 2011 IEEE International Workshop on Machine Learning for Signal Processing.

Designer networks for time series processing

Lars Kai Hansen, Jan Larsen, Carl Edward Rasmussen, 1993, Neural Networks for Signal Processing III - Proceedings of the 1993 IEEE-SP Workshop.

It's Who You Know: Second-Order Mixing in Networks

Ingemar J. Cox, Lars Kai Hansen, Shi Zhou, 2009 .

Sparse Source EEG Imaging with the Variational Garrote

Lars Kai Hansen, Sofie Therese Hansen, Carsten Stahlhut, 2013, 2013 International Workshop on Pattern Recognition in Neuroimaging.

Visualization of neural networks using saliency maps

Lars Kai Hansen, Niels J. S. Mørch, Stephen C. Strother, 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

Fusing Simultaneous EEG and fMRI Using Functional and Anatomical Information

Klaus-Robert Müller, Lars Kai Hansen, Sofie Therese Hansen, 2015, 2015 International Workshop on Pattern Recognition in NeuroImaging.

Semi-Supervised Sleep-Stage Scoring Based on Single Channel EEG

Lars Kai Hansen, A. M. Munk, K. V. Olesen, 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Sparse but emotional decomposition of lyrics

Lars Kai Hansen, Michael Kai Petersen, Morten Mørup, 2009 .

The Role of Top-Down Attention in the Cocktail Party: Revisiting Cherry's Experiment after Sixty Years

Lars Kai Hansen, Jan Larsen, Letizia Marchegiani, 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.

MONAURAL ICA OF WHITE NOISE MIXTURES IS HARD

Kaare Brandt Petersen, Lars Kai Hansen, 2003 .

EEG Sequence Imaging: A Markov Prior for the Variational Garrote

Lars Kai Hansen, Sofie Therese Hansen, 2013, NIPS 2013.

CICAAR: Convolutive ICA with an Auto-regressive Inverse Model

Lars Kai Hansen, Mads Dyrholm, 2004, ICA.

Vocal Segment Classification in Popular Music

Lars Kai Hansen, Ling Feng, Andreas Brinch Nielsen, 2008, ISMIR.

Spatio temporal media components for neurofeedback

Lars Kai Hansen, Arkadiusz Stopczynski, Jakob Eg Larsen, 2013, 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW).

A probabilistic framework for classification of dermatoscopic images

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 1999 .

A hierarchical Bayesian M/EEG imagingmethod correcting for incomplete spatio-temporal priors

Lars Kai Hansen, David P. Wipf, Hagai Attias, 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.

Revisiting Boltzmann learning: parameter estimation in Markov random fields

Lars Kai Hansen, Jan Larsen, Ulrik Kjems, 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

Cross validation in LULOO

Lars Kai Hansen, Paul Haase Sørensen, Jan Larsen, 1996 .

Lars Kai Hansen, Finn Årup Nielsen, L. K. Hansen, 2004, Artif. Intell. Medicine.

Pruning from Adaptive Regularization

Carl E. Rasmussen, Lars Kai Hansen, L. K. Hansen, 1994, Neural Computation.

Ensemble methods for handwritten digit recognition

Lars Kai Hansen, Peter Salamon, C. Liisberg, 1992, Neural Networks for Signal Processing II Proceedings of the 1992 IEEE Workshop.

PET Reconstruction with a Markov Random Field Prior

Lars Kai Hansen, L. K. Hansen, Peter A. Philipsen, 2001 .

A Neural Network Model of the Visual Short-Term Memory

Lars Kai Hansen, Anders Petersen, Søren Kyllingsbæk, 2009 .

Early stop criterion from the bootstrap ensemble

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Mapping from Speech to Images Using Continuous State Space Models

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 2004, MLMI.

Modeling the hemodynamic response in fMRI using smooth FIR filters

Lars Kai Hansen, Finn Årup Nielsen, Cyril Goutte, 2000, IEEE Transactions on Medical Imaging.

Bayesian Averaging is Well-Temperated

Lars Kai Hansen, L. K. Hansen, 1999, NIPS.

Unified ICA-SPM Analysis of fMRI Experiments - Implementation of an ICA Graphical user Interface for the SPM Pipeline

Lars Kai Hansen, Kristoffer Hougaard Madsen, Troels Bjerre, 2009, BIOSIGNALS.

Color segmentation of skin lesions with the generalizable Gaussian mixture model

Lars Kai Hansen, Sigurdur Sigurdsson, Krzysztof Drzewiecki, 2003 .

Cognitive semantic networks: Emotional verbs throw a tantrum but don't bite

Lars Kai Hansen, Michael Kai Petersen, L. K. Hansen, 2012, 2012 3rd International Workshop on Cognitive Information Processing (CIP).

Ensemble Learning and Linear Response Theory for ICA

Ole Winther, Lars Kai Hansen, Pedro A. d. F. R. Højen-Sørensen, 2000, NIPS.

Empirical generalization assessment of neural network models

Lars Kai Hansen, Jan Larsen, J. Larsen, 1995, Proceedings of 1995 IEEE Workshop on Neural Networks for Signal Processing.

Webmining: learning from the world wide web

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 2002 .

Bayesian and non-Bayesian techniques applied to censored survival data with missing values

Ole Winther, Lars Kai Hansen, L. K. Hansen, 2007 .

How efficient is estimation with missing data?

Lars Kai Hansen, Jan Larsen, Letizia Marchegiani, 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Model Selection for Gaussian Kernel PCA Denoising

Lars Kai Hansen, L. K. Hansen, Kasper Winther Jørgensen, 2012, IEEE Transactions on Neural Networks and Learning Systems.

Probably Approximately Correct Search

Ingemar J. Cox, Lars Kai Hansen, Ruoxun Fu, 2009, ICTIR.

Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation

John W. Fisher, Lars Kai Hansen, Søren Hauberg, 2015, AISTATS.

Non-parametric co-clustering of large scale sparse bipartite networks on the GPU

Lars Kai Hansen, Morten Mørup, L. K. Hansen, 2011, 2011 IEEE International Workshop on Machine Learning for Signal Processing.

Deterministic modularity optimization

Lars Kai Hansen, Sune Lehmann, 2007 .

Robustness analytics to data heterogeneity in edge computing

Lars Kai Hansen, Xenofon Fafoutis, Hari Mohan Pandey, 2020, Comput. Commun..

Experiences with Matlab and VRML in Functional Neuroimaging Visualizations

Lars Kai Hansen, L. K. Hansen, Arup Nielsen, 1999 .

Joint Modelling of Structural and Functional Brain Networks

Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup, 2012, NIPS 2012.

What to measure next to improve decision making? On top-down task driven feature saliency

Lars Kai Hansen, Letizia Marchegiani, Seliz G. Karadogan, 2011, 2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB).

Bayesian Inference for Spatio-temporal Spike-and-Slab Priors

Ole Winther, Aki Vehtari, Lars Kai Hansen, 2015, J. Mach. Learn. Res..

On the Limits to Multi-Modal Popularity Prediction on Instagram - A New Robust, Efficient and Explainable Baseline pdf

Lars Kai Hansen, Damian Konrad Kowalczyk, Christoffer Riis, 2020, ICAART.

Interpretability in Intelligent Systems - A New Concept?

Lars Kai Hansen, Laura Rieger, L. K. Hansen, 2019, Explainable AI.

On the Slow Convergence of EM and VBEM in Low-Noise Linear Models

Kaare Brandt Petersen, Ole Winther, Lars Kai Hansen, 2005, Neural Computation.

Get mobile - The Smartphone Brain Scanner

Lars Kai Hansen, Arkadiusz Stopczynski, Jakob Eg Larsen, 2012, EMBC 2012.

Pruning the vocabulary for better context recognition

Lars Kai Hansen, R. E. Madsen, Jan Larsen, 2004 .

Identifying modular relations in complex brain networks

Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup, 2012, 2012 IEEE International Workshop on Machine Learning for Signal Processing.

Enhancing the Multivariate Signal of [15O] water PET Studies with a New Non-Linear Neuroanatomical Registration Algorithm

Lars Kai Hansen, Stephen C. Strother, Ian Law, 1999, IEEE Trans. Medical Imaging.

Blind detection of independent dynamic components

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

Mining for associations between text and brain activation in a functional neuroimaging database

Lars Kai Hansen, Finn Årup Nielsen, Daniela Balslev, 2007, Neuroinformatics.

Detection of skin cancer by classification of Raman spectra

Lars Kai Hansen, Jan Larsen, Monika Gniadecka, 2004, IEEE Transactions on Biomedical Engineering.

Sonar discrimination of cylinders from different angles using neural networks

Lars Kai Hansen, Jan Larsen, Whitlow W. L. Au, 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

Visualization of nonlinear kernel models in neuroimaging by sensitivity maps

Lars Kai Hansen, Kristoffer Hougaard Madsen, Peter Mondrup Rasmussen, 2011, NeuroImage.

Recurrent Networks: Second Order Properties and Pruning

Lars Kai Hansen, L. K. Hansen, Morten With Pedersen, 1994, NIPS.

Adaptive Regularization in Neural Network Modeling

Lars Kai Hansen, Jan Larsen, Claus Svarer, 2012, Neural Networks: Tricks of the Trade.

Chapter 73 - [ 15 O]Water PET More “Noise” Than Signal?

Lars Kai Hansen, Stephen C. Strother, David A. Rottenberg, 1996 .

Towards end-to-end optimisation of functional image analysis pipelines pdf

Lars Kai Hansen, Kristoffer Hougaard Madsen, Albert Vilamala, 2016, ArXiv.

A Smartphone Interface for a Wireless EEG Headset with Real-Time 3D Reconstruction

Lars Kai Hansen, Arkadiusz Stopczynski, Jakob Eg Larsen, 2011, ACII.

Neural Network Ensembles

Lars Kai Hansen, Peter Salamon, L. K. Hansen, 1990, IEEE Trans. Pattern Anal. Mach. Intell..

Comments for: Rivals, I., & Personnaz, L. (2000). Construction of confidence intervals for neural networks based on least squares estimation. Neural Networks, 13, 463-484.

Lars Kai Hansen, Jan Larsen, 2002, Neural networks : the official journal of the International Neural Network Society.

Parallel Factor Analysis as an exploratory tool for wavelet transformed event-related EEG

Lars Kai Hansen, Morten Mørup, Josef Parnas, 2006, NeuroImage.

Author cocitation analysis of articles from “Neurolmage”

Lars Kai Hansen, Finn Årup Nielsen, 2001, NeuroImage.

Learning with Uncertainty - Gaussian Processes and Relevance Vector Machines

Lars Kai Hansen, L. K. Hansen, Joaquin Quinonero Candela, 2004 .

Model Structure Selection in Convolutive Mixtures

Lars Kai Hansen, Scott Makeig, Mads Dyrholm, 2006, ICA.

On design and evaluation of tapped-delay neural network architectures

Lars Kai Hansen, Jan Larsen, Claus Svarer, 1993, IEEE International Conference on Neural Networks.

NIPS Workshop: Advances in Acoustic Models

Lars Kai Hansen, Ling Feng, 2006, NIPS 2006.

Dual EEG of social interaction: a machine learning approach to the two-brain problem

Lars Kai Hansen, Ivana Konvalinka, Christopher D. Frith, 2012 .

Generalization performance of regularized neural network models

Lars Kai Hansen, Jan Larsen, J. Larsen, 1994, Proceedings of IEEE Workshop on Neural Networks for Signal Processing.

Sparse non-linear denoising: Generalization performance and pattern reproducibility in functional MRI

Lars Kai Hansen, L. K. Hansen, Trine Julie Abrahamsen, 2011, Pattern Recognit. Lett..

Learning and clean-up in a large scale music database

Kaare Brandt Petersen, Lars Kai Hansen, Søren Holdt Jensen, 2007, 2007 15th European Signal Processing Conference.

Fast sampling from a Hidden Markov Model posterior for large data

Lars Kai Hansen, Rasmus Bonnevie, 2014, 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

A prediction matrix approach to convolutive ICA

Lars Kai Hansen, Mads Dyrholm, M. Dyrholm, 2003, 2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718).

Use and Subtleties of Saddlepoint Approximation for Minimum Mean-Square Error Estimation

Lars Kai Hansen, Albert H. Nuttall, Thomas Beierholm, 2008, IEEE Transactions on Information Theory.

Computer-Based Methods for Data Handling, Processing, and Analysis

Lars Kai Hansen, Kristoffer Hougaard Madsen, Finn Årup Nielsen, 2006 .

An Artificial Neural Network Approach to Estimation of the Regional Glucose Metabolism Using PET

Lars Kai Hansen, Olaf B. Paulson, Claus Svarer, 1996 .

Towards Federated Learning: Robustness Analytics to Data Heterogeneity pdf

Lars Kai Hansen, Xenofon Fafoutis, Jia Qian, 2020, ArXiv.

Modelling Strategies for Functional Magnetic Resonance Imaging

Lars Kai Hansen, Karam Sidaros, Kristoffer Hougaard Madsen, 2009 .

Software for Creating and Analyzing Semantic Representations

Lars Kai Hansen, Finn Årup Nielsen, L. K. Hansen, 2020 .

Controlled Growth of Cascade Correlation Nets

Lars Kai Hansen, 1994 .

Scientific discovery using genetic programming

Maarten Keijzer, Lars Kai Hansen, 2001 .

Bayesian Modelling of fMRI lime Series

Carl E. Rasmussen, Lars Kai Hansen, Pedro A. d. F. R. Højen-Sørensen, 1999, NIPS.

Latent Causal Modelling of Neuroimaging Data

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2009, NIPS 2009.

Time series prediction based on the Relevance Vector Machine with adaptive kernels

Joaquin Quiñonero Candela, Lars Kai Hansen, L. K. Hansen, 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Improving Query Correctness Using Centralized Probably Approximately Correct (PAC) Search

Ingemar J. Cox, Lars Kai Hansen, Jianhan Zhu, 2010, ECIR.

A spatially robust ICA algorithm for multiple fMRI data sets

Lars Kai Hansen, Stephen C. Strother, Miles N. Wernick, 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

ERPWAVELAB A toolbox for multi-channel analysis of time–frequency transformed event related potentials

Lars Kai Hansen, Morten Mørup, L. K. Hansen, 2007, Journal of Neuroscience Methods.

IROF: a low resource evaluation metric for explanation methods pdf

Lars Kai Hansen, Laura Rieger, L. K. Hansen, 2020, ArXiv.

Simultaneous EEG Source and Forward Model Reconstruction (SOFOMORE) Using a Hierarchical Bayesian Approach

Ole Winther, Lars Kai Hansen, Morten Mørup, 2011, J. Signal Process. Syst..

Probabilistic blind deconvolution of non-stationary sources

Lars Kai Hansen, Rasmus Kongsgaard Olsson, R. Olsson, 2004, 2004 12th European Signal Processing Conference.

Algorithms for Source Separation - with Cocktail Party Applications

Lars Kai Hansen, L. K. Hansen, Rasmus Kongsgaard, 2016 .

The Dangers of Following Trends in Research: Sparsity and Other Examples of Hammers in Search of Nails

Vince D. Calhoun, Lars Kai Hansen, Tülay Adali, 2018, Proc. IEEE.

Privacy for Personal Neuroinformatics pdf

Alex Pentland, Lars Kai Hansen, Arkadiusz Stopczynski, 2014, ArXiv.

Adaptive Text Entry for Mobile Devices

Lars Kai Hansen, Nette Schultz, L. K. Hansen, 2009 .

Context based multimedia information retrieval

Lars Kai Hansen, Jan Larsen, Lasse Lohilahti Mølgaard, 2009 .

Clustering of Sun exposure measurements

Lars Kai Hansen, Jan Larsen, Hans-Christian Wulf, 2002, Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing.

On Phonemes As Cognitive Components of Speech

Lars Kai Hansen, Ling Feng, Ling Feng, 2008 .

Sparseness in predictive models is associated with reduced pattern reproducibility

Lars Kai Hansen, Kristoffer Hougaard Madsen, Peter Mondrup Rasmussen, 2010 .

A regularized matrix factorization approach to induce structured sparse-low-rank solutions in the EEG inverse problem

Lars Kai Hansen, Antonio Artés-Rodríguez, Massimiliano Pontil, 2014, EURASIP Journal on Advances in Signal Processing.

Data mining a functional neuroimaging database for functional segregation in brain regions

Lars Kai Hansen, Finn Årup Nielsen, Daniela Balslev, 2006 .

Forward Models can be Inferred from EEG Data

Lars Kai Hansen, Søren Hauberg, Sofie Therese Hansen, 2016 .

Kernel Multivariate Analysis Framework for Supervised Subspace Learning: A Tutorial on Linear and Kernel Multivariate Methods

Kaare Brandt Petersen, Lars Kai Hansen, Gustavo Camps-Valls, 2013, IEEE Signal Processing Magazine.

Neural Networks in Functional Neuroimaging

Lars Kai Hansen, Finn Årup Nielsen, Niels Mørch, 1998 .

Bayesian Model Comparison in Nonlinear BOLD fMRI Hemodynamics

Lars Kai Hansen, Kristoffer Hougaard Madsen, L. K. Hansen, 2008, Neural Computation.

Comparison of two convolution models for fMRI time series

Bruce R. Rosen, Lars Kai Hansen, Egill Rostrup, 1997 .

Introduction to the Issue on fMRI Analysis for Human Brain Mapping

Vince D. Calhoun, Martin J. McKeown, Z. Jane Wang, 2008, IEEE J. Sel. Top. Signal Process..

Bayesian Inference for Structured Spike and Slab Priors

Ole Winther, Lars Kai Hansen, Michael Riis Andersen, 2014, NIPS.

Tomographic reconstruction using anatomy and regularization

Lars Kai Hansen, Esben Høgh-Rasmussen, 2006 .

Generalizable Singular Value Decomposition for Ill-posed Datasets

Lars Kai Hansen, Stephen C. Strother, Ulrik Kjems, 2000, NIPS.

Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner’s Handbook

Niels Kjølstad Poulsen, Lars Kai Hansen, Ole Ravn, 2000 .

FindZebra: A search engine for rare diseases

Ole Winther, Ingemar J. Cox, Christina Lioma, 2013, Int. J. Medical Informatics.

Sound Search Engine Concept

Kaare Brandt Petersen, Lars Kai Hansen, Sigurdur Sigurdsson, 2006 .

Networking real and virtual brains

Lars Kai Hansen, 2004 .

Universal Distribution of Saliencies for Pruning in Layered Neural Networks

Lars Kai Hansen, Benny Lautrup, Jan Gorodkin, 1997, Int. J. Neural Syst..

Compact web browsing profiles for click-through rate prediction

Lars Kai Hansen, Bjarne Ørum Fruergaard, L. K. Hansen, 2014, 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

Adaptive regularization of noisy linear inverse problems

Lars Kai Hansen, Kristoffer Hougaard Madsen, L. K. Hansen, 2006, 2006 14th European Signal Processing Conference.

Frequency constrained ShiftCP modeling of neuroimaging data

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2011, 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

Lucas C. Parra, Lars Kai Hansen, Simon Kamronn, 2014, 2014 International Workshop on Pattern Recognition in Neuroimaging.

Variance inflation in high dimensional Support Vector Machines

Lars Kai Hansen, L. K. Hansen, Trine Julie Abrahamsen, 2013, Pattern Recognit. Lett..

A framework for closed-loop neurofeedback for real-time EEG decoding

Lars Kai Hansen, Sofie Therese Hansen, L. K. Hansen, 2019 .

Probabilistic M/EEG source imaging from sparse spatio-temporal event structure

Lars Kai Hansen, Srikantan S. Nagarajan, Carsten Stahlhut, 2012, NIPS 2012.

Large-scale Machine Learning in High-dimensional Datasets

Lars Kai Hansen, L. K. Hansen, Toke Jansen Hansen, 2013 .

Dimensionality reduction for click-through rate prediction: Dense versus sparse representation pdf

Lars Kai Hansen, Bjarne Ørum Fruergaard, L. K. Hansen, 2013, NIPS 2013.

Adaptive smoothing in fMRI data processing neural networks

Lars Kai Hansen, Kristoffer Hougaard Madsen, Albert Vilamala, 2017, 2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Large scale topic modeling made practical

Lars Kai Hansen, Bjarne Ørum Wahlgreen, 2011, 2011 IEEE International Workshop on Machine Learning for Signal Processing.

Hemodynamic modelling of BOLD fMRI - A machine learning approach

Lars Kai Hansen, Danjal Jakup Jacobsen, L. K. Hansen, 2007 .

MuZeeker: Adapting a Music Search Engine for Mobile Phones

Lars Kai Hansen, Jakob Eg Larsen, Søren Halling, 2008, WMMP.

Analysis of functional neuroimages using ICA with adaptive binary sources

Ole Winther, Lars Kai Hansen, Pedro A. d. F. R. Højen-Sørensen, 2002, Neurocomputing.

Shift-invariant multilinear decomposition of neuroimaging data

Lars Kai Hansen, Morten Mørup, Kristoffer Hougaard Madsen, 2008, NeuroImage.

Mobile real-time EEG imaging Bayesian inference with sparse, temporally smooth source priors

Lars Kai Hansen, Sofie Therese Hansen, Carsten Stahlhut, 2013, 2013 International Winter Workshop on Brain-Computer Interface (BCI).

Independent Component Analysis in Multimedia Modeling

Lars Kai Hansen, Shun-ichi Amari, Jan Larsen, 2003 .

Automatic anatomical labeling of Talairach coordinates and generation of volumes of interest via the BrainMap database

Lars Kai Hansen, Finn Årup Nielsen, L. K. Hansen, 2008 .

Regularized Pre-image Estimation for Kernel PCA De-noising

Lars Kai Hansen, L. K. Hansen, Trine Julie Abrahamsen, 2011, J. Signal Process. Syst..

Detecting hierarchical structure in networks

Lars Kai Hansen, Morten Mørup, Mikkel N. Schmidt, 2012, 2012 3rd International Workshop on Cognitive Information Processing (CIP).

Deep convolutional neural networks for interpretable analysis of EEG sleep stage scoring

Lars Kai Hansen, Kristoffer Hougaard Madsen, L. K. Hansen, 2017, 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP).

Optimizing the fMRI data-processing pipeline using prediction and reproducibility performance metrics: I. A preliminary group analysis

Lars Kai Hansen, Jon Anderson, David Rottenberg, 2004, NeuroImage.

Control with Neural Networks

Niels Kjølstad Poulsen, Lars Kai Hansen, Ole Ravn, 2000 .

The Evaluation of Preprocessing Choices in Single-Subject BOLD fMRI Using NPAIRS Performance Metrics

Essa Yacoub, Lars Kai Hansen, Stephen C. Strother, 2003, NeuroImage.

Outlier estimation and detection application to skin lesion classification

Lars Kai Hansen, Jan Larsen, Sigurður Sigurðsson, 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Algorithms for Sparse Nonnegative Tucker Decompositions

Lars Kai Hansen, Morten Mørup, L. K. Hansen, 2008, Neural Computation.

Unsupervised learning and generalization

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

Blind Separation of Noisy Mixtures

Lars Kai Hansen, L. K. Hansen, 1998 .

Single-Trial Decoding of Scalp EEG Under Naturalistic Stimuli

Nicolai Pedersen, Lars Kai Hansen, Sofie Therese Hansen, 2018, bioRxiv.

Semantic Contours in Tracks Based on Emotional Tags

Lars Kai Hansen, Michael Kai Petersen, Andrius Butkus, 2009, CMMR.

Signal Detection Using Ica: Application to Chat Room Topic Spotting

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 2002 .

Structured sparsity regularization approach to the EEG inverse problem

Lars Kai Hansen, Antonio Artés-Rodríguez, Massimiliano Pontil, 2012, 2012 3rd International Workshop on Cognitive Information Processing (CIP).

Combining embedding methods for a word intrusion task

Lars Kai Hansen, Finn Årup Nielsen, 2019, KONVENS.

Testing Multimodal Integration Hypotheses with Application to Schizophrenia Data

Lars Kai Hansen, Nikolaj Bak, Martin C. Axelsen, 2015, 2015 International Workshop on Pattern Recognition in NeuroImaging.

Adaptive tools in virtual environments: Independent component analysis for multimedia

Lars Kai Hansen, Jan Larsen, Niels Jørgen Christensen, 2002 .

What can we learn from gradients? pdf

Lars Kai Hansen, Jia Qian, 2020, ArXiv.

Integration of top-down and bottom-up information for audio organization and retrieval

Lars Kai Hansen, Jan Larsen, Bjørn Sand Jensen, 2012 .

Sparse Kernel Orthonormalized PLS for feature extraction in large data sets

Kaare Brandt Petersen, Lars Kai Hansen, Jerónimo Arenas-García, 2006, NIPS.

Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior

Lars Kai Hansen, Sofie Therese Hansen, L. K. Hansen, 2017, NeuroImage.

A Locally Adaptive Normal Distribution

Lars Kai Hansen, Søren Hauberg, Georgios Arvanitidis, 2016, NIPS.

A Fast Kernel Based Searchlight Heuristic for Real-time fMRI

Lars Kai Hansen, Toke Jansen Hansen, Kristoffer H Madsen, 2010 .

On Independent Component Analysis for Multimedia Signals

Lars Kai Hansen, Jan Larsen, L. K. Hansen, 2000 .

Statistical learning for predictive targeting in online advertising

Lars Kai Hansen, Bjarne Ørum Fruergaard, Jesper Urban, 2015 .

Non-parametric Bayesian graph models reveal community structure in resting state fMRI

Hartwig R. Siebner, Lars Kai Hansen, Morten Mørup, 2014, NeuroImage.

A Quantitative Study Of Pruning By Optimal Brain Damage

Ole Winther, Lars Kai Hansen, Claus Svarer, 1993, Int. J. Neural Syst..

Consensus Inference in Neuroimaging

Lars Kai Hansen, Stephen C. Strother, Finn Årup Nielsen, 2001, NeuroImage.

Hierarchical Clustering for Datamining

Lars Kai Hansen, Jan Larsen, Anna Szymkowiak, 2001 .

Coordinate-based Meta-analytic search for the SPM Neuroimaging Pipeline - The BredeQuery Plugin for SPM5

Lars Kai Hansen, Finn Årup Nielsen, Bartlomiej Wilkowski, 2009, HEALTHINF.

On the Limits to Multi-Modal Popularity Prediction on Instagram - A New Robust, Efficient and Explainable Baseline

Lars Kai Hansen, Christoffer Riis, Damian Konrad Kowalczyk, 2021, ICAART.

Generalization by design: Shortcuts to Generalization in Deep Learning pdf

Lars Kai Hansen, L. K. Hansen, Petr Taborsky, 2021, ArXiv.

Topic Model Robustness to Automatic Speech Recognition Errors in Podcast Transcripts pdf

Lars Kai Hansen, Lucas Chaves Lima, Raluca Alexandra Fetic, 2021, ArXiv.

Real-Time Decoding of Attentional States Using Closed-Loop EEG Neurofeedback

Lars Kai Hansen, Sofie Therese Hansen, L. K. Hansen, 2021, Neural Computation.

Input space regularization stabilizes pre-images for kernel PCA de-noising

Lars Kai Hansen, L. K. Hansen, Trine Julie Abrahamsen, 2009, 2009 IEEE International Workshop on Machine Learning for Signal Processing.

Neural Markers of Responsiveness to the Environment in Human Sleep

Lars Kai Hansen, Andreas Trier Poulsen, Thomas Andrillon, 2016, The Journal of Neuroscience.

Mining Posterior Cingulate

Lars Kai Hansen, Finn Årup Nielsen, Daniela Balslev, 2004 .

The Polish Academy of Sciences

Takao Hinamoto, Pascal Frossard, Paavo Alku, 1961, Nature.

Real-time monitoring of sentiment in business related Wikipedia articles

Lars Kai Hansen, Finn Årup Nielsen, 2013 .

Fitness-functions of Genetic Algorithms for optimizingNeural Network topologiesGunnar

Lars Kai Hansen, L. K. Hansen, 1995 .

How many Principal Components

Bruce R. Rosen, Lars Kai Hansen, Egill Rostrup, 1997 .

Modeling of locations in the BrainMap database: Detection of outliers

Lars Kai Hansen, Finn Årup Nielsen, Ulrik Kjems, 2001, NeuroImage.

Approximating methods for intractable probabilistic models: Applications in neuroscience

Lars Kai Hansen, Jan Larsen, Pedro A. d. F. R. Højen-Sørensen, 2002 .

Growth-rate regulated genes have profound impact on interpretation of transcriptome profiling in Saccharomyces cerevisiae

Ole Winther, Lars Kai Hansen, Søren Brunak, 2006, Genome Biology.

The Smartphone Brain Scanner: A Portable Real-Time Neuroimaging System

Lars Kai Hansen, Arkadiusz Stopczynski, Jakob Eg Larsen, 2013, PloS one.

Regularity increases middle latency evoked and late induced beta brain response following proprioceptive stimulation

Lars Kai Hansen, Morten Mørup, Josef Parnas, 2008, Brain Research.

Specialized tools are needed when searching the web for rare disease diagnoses

Ole Winther, Ingemar J. Cox, Christina Lioma, 2013, Rare diseases.

Testing for difference between two groups of functional neuroimaging experiments

Lars Kai Hansen, Andrew C. N. Chen, Finn Årup Nielsen, 2004 .

A Probabilistic Framework for Detection of Skin Cancer by Raman Spectra

Lars Kai Hansen, Jan Larsen, Sigurdur Sigurdsson, 2003 .

Spatio-temporal spike and slab priors for MMV problems

Ole Winther, Lars Kai Hansen, Michael Riis Andersen, 2015 .

Estimating and suppressing background in Raman spectra with an artificial neural network

Lars Kai Hansen, Jan Larsen, Sigurdur Sigurdsson, 2003 .

Massive Weight Sharing: A Cure For Extremely Ill-Posed Problems

Lars Kai Hansen, Benny Lautrup, L. K. Hansen, 1994 .

Evaluating preprocessing choices in single-subject BOLD-fMRI studies using data-driven performance metrics

Lars Kai Hansen, Stephen LaConte, David Rottenberg, 2001, NeuroImage.

Measuring Activation Pattern Reproducibility Using Resampling Techniques

Lars Kai Hansen, Stephen C. Strother, Kelly Rehm, 1998 .

Proprioceptive evoked gamma oscillations

Lars Kai Hansen, Morten Mørup, Josef Parnas, 2007, Brain Research.

Convolutive ICA for Spatio-Temporal Analysis of EEG

Lars Kai Hansen, Scott Makeig, L. K. Hansen, 2005 .

MEAN FIELD IMPLEMENTATION OF BAYESIAN ICA

Ole Winther, Lars Kai Hansen, Pedro Hojen-Sorensen, 2001 .

Assessing the reproducibility in sets of Talairach coordinates

Lars Kai Hansen, Finn Årup Nielsen, .

Blind Separation of Noisy Image Mixtures

Lars Kai Hansen, L. K. Hansen, L. K. Hansen, 2000 .