Jörg Lücke

发表

Beyond Manual Tuning of Hyperparameters

Lars Schmidt-Thieme, Frank Hutter, Jörg Lücke, 2015, KI - Künstliche Intelligenz.

Rapid Processing and Unsupervised Learning in a Model of the Cortical Macrocolumn

Jörg Lücke, Christoph von der Malsburg, C. Malsburg, 2004, Neural Computation.

Truncated Variational Expectation Maximization

Jörg Lücke, 2016 .

L G ] 4 M ar 2 02 0 Maximal Causes for Exponential Family Observables

Jörg Lücke, S. H. Mousavi, Jakob Drefs, 2020 .

A Truncated Variational EM Approach for Spike-and-Slab Sparse Coding

J. Shelton, Jörg Lücke, Abdul-Saboor Sheikh, 2012 .

Hysteresis effects on the input–output curve of motor evoked potentials

U. Ziemann, Jörg Lücke, N. Arai, 2009, Clinical Neurophysiology.

The Evidence Lower Bound of Variational Autoencoders Converges to a Sum of Three Entropies

Zhenwen Dai, Jörg Lücke, D. Forster, 2020, ArXiv.

A Variational EM Acceleration for Efficient Clustering at Very Large Scales

Jörg Lücke, F. Hirschberger, D. Forster, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Evolutionary Variational Optimization of Generative Models

Jörg Lücke, Jakob Drefs, E. Guiraud, 2020, J. Mach. Learn. Res..

Inference and Learning in a Latent Variable Model for Beta Distributed Interval Data

Jörg Lücke, Enrico Guiraud, Jakob Drefs, 2021, Entropy.

A Double-Dictionary Approach Learns Component Means and Variances for V1 Encoding

Jörg Lücke, Jakob Drefs, S. Hamid Mousavi, 2020, LOD.

STRFs in primary auditory cortex emerge from masking-based statistics of natural sounds

Richard E. Turner, Zhenwen Dai, Jörg Lücke, 2019, PLoS Comput. Biol..

Evolutionary expectation maximization

Jörg Lücke, Enrico Guiraud, Jakob Drefs, 2018, GECCO.

Data-driven methods reveal the generalizing mechanisms of speech processing in naturally varying soundscapes

Jörg Lücke, Moritz Boos, Jochem Rieger, 2018 .

Binary Non-Negative Matrix Deconvolution for Audio Dictionary Learning

Jörg Lücke, Szymon Drgas, Tuomas Virtanen, 2017, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

GP-Select: Accelerating EM Using Adaptive Subspace Preselection

Arthur Gretton, Zhenwen Dai, Jörg Lücke, 2014, Neural Computation.

Select-and-Sample for Spike-and-Slab Sparse Coding

Jörg Lücke, Abdul-Saboor Sheikh, Jörg Lücke, 2016, NIPS.

Nonlinear Spike-And-Slab Sparse Coding for Interpretable Image Encoding

Jörg Lücke, Jörg Bornschein, Abdul-Saboor Sheikh, 2015, PloS one.

A truncated EM approach for spike-and-slab sparse coding

Jörg Lücke, Abdul-Saboor Sheikh, Jacquelyn A. Shelton, 2012, J. Mach. Learn. Res..

Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study

Jörg Lücke, Jörg Bornschein, Marc Henniges, 2013, PLoS Comput. Biol..

Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding

Jörg Lücke, Jörg Bornschein, Abdul-Saboor Sheikh, 2012, NIPS.

The Maximal Causes of Natural Scenes are Edge Filters

Jörg Lücke, Jörg Bornschein, Gervasio Puertas, 2010, NIPS.

Generalizable dimensions of human cortical auditory processing of speech in natural soundscapes: A data-driven ultra high field fMRI approach

Jörg Lücke, Jochem W. Rieger, Moritz Boos, 2021, NeuroImage.

Closed-Form EM for Sparse Coding and Its Application to Source Separation

Jörg Lücke, Abdul-Saboor Sheikh, Jörg Lücke, 2011, LVA/ICA.

A Closed-Form EM Algorithm for Sparse Coding

Jörg Lücke, Abdul-Saboor Sheikh, Jörg Lücke, 2011 .

Binary Sparse Coding

Julian Eggert, Jörg Lücke, Jörg Bornschein, 2010, LVA/ICA.

Expectation Truncation and the Benefits of Preselection In Training Generative Models

Julian Eggert, Jörg Lücke, J. Eggert, 2010, J. Mach. Learn. Res..

Maximal Causes for Non-linear Component Extraction

Jörg Lücke, Maneesh Sahani, M. Sahani, 2008, J. Mach. Learn. Res..

k-means as a variational EM approximation of Gaussian mixture models

Jörg Lücke, Dennis Forster, Jörg Lücke, 2017, Pattern Recognit. Lett..

Optimal neural inference of stimulus intensities

Jörg Lücke, Cristina Savin, Travis Monk, 2018, Scientific Reports.

Truncated Variational Sampling for 'Black Box' Optimization of Generative Models

Zhenwen Dai, Jörg Lücke, Georgios Exarchakis, 2017, LVA/ICA.

Phase transition for parameter learning of hidden Markov models.

Alexander K. Hartmann, Jorg Lucke, Nikita Rau, 2020, Physical review. E.

Models of Acetylcholine and Dopamine Signals Differentially Improve Neural Representations

Jörg Lücke, Klaus Obermayer, Raphaël Holca-Lamarre, 2017, Front. Comput. Neurosci..

Autonomous Document Cleaning—A Generative Approach to Reconstruct Strongly Corrupted Scanned Texts

Zhenwen Dai, Jörg Lücke, 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Efficient occlusive components analysis

Richard E. Turner, Julian Eggert, Jörg Lücke, 2014, J. Mach. Learn. Res..

Autonomous cleaning of corrupted scanned documents — A generative modeling approach

Zhenwen Dai, Jörg Lücke, Zhenwen Dai, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Receptive Field Self-Organization in a Model of the Fine Structure in V1 Cortical Columns

Jörg Lücke, Jörg Lücke, 2009, Neural Computation.

Generalized Softmax Networks for Non-linear Component Extraction

Jörg Lücke, Maneesh Sahani, M. Sahani, 2007, ICANN.

Hierarchical self-organization of minicolumnar receptive fields

Jörg Lücke, Jörg Lücke, 2004, Neural Networks.

Visualization of SARS-CoV-2 Infection Scenes by ‘Zero-Shot’ Enhancements of Electron Microscopy Images

Jörg Lücke, Jakob Drefs, Sebastian Salwig, 2021, bioRxiv.

A recurrent dynamic model for correspondence-based face recognition.

Christian Wolff, Jörg Lücke, Philipp Wolfrum, 2008, Journal of vision.

Macrocolumns as Decision Units

Rolf P. Würtz, Jörg Lücke, Christoph von der Malsburg, 2002, ICANN.

Feedforward Inhibition and Synaptic Scaling – Two Sides of the Same Coin?

Jörg Lücke, Cristina Savin, Christian Keck, 2012, PLoS Comput. Biol..

Maximal Causes for Exponential Family Observables pdf

Jörg Lücke, Jakob Drefs, S. Hamid Mousavi, 2020, ArXiv.

Beyond Manual Tuning of Hyperparameters

F. Hutter, L. Schmidt-Thieme, Jörg Lücke, 2015, KI - Künstliche Intelligenz.

Rapid Convergence to Feature Layer Correspondences

Jörg Lücke, Christoph von der Malsburg, Christian Keck, 2008, Neural Computation.

Rapid Correspondence Finding in Networks of Cortical Columns

Jörg Lücke, Christoph von der Malsburg, C. Malsburg, 2006, ICANN.

Select and Sample - A Model of Efficient Neural Inference and Learning

Jörg Lücke, Jörg Bornschein, Abdul-Saboor Sheikh, 2011, NIPS.

Automated detection of circulating tumor cells with naive Bayesian classifiers

Carl-Magnus Svensson, Solveigh Krusekopf, Jörg Lücke, 2014, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

Glial cells for information routing?

Jörg Lücke, Christoph von der Malsburg, Caroline Möller, 2007, Cognitive Systems Research.

Dynamics of Cortical Columns - Sensitive Decision Making

Jörg Lücke, Jörg Lücke, 2005, ICANN.

Neural Simpletrons: Learning in the Limit of Few Labels with Directed Generative Networks

Jörg Lücke, Abdul-Saboor Sheikh, Dennis Forster, 2015, Neural Computation.

Truncated variational EM for semi-supervised neural simpletrons

Jörg Lücke, Dennis Forster, Jörg Lücke, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents

Jörg Lücke, Jakob Drefs, E. Guiraud, 2020, ECML/PKDD.

Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means

Jörg Lücke, Dennis Forster, Jörg Lücke, 2017, AISTATS.

Accelerated Training of Large-Scale Gaussian Mixtures by a Merger of Sublinear Approaches pdf

Jörg Lücke, Dennis Forster, Florian Hirschberger, 2018, ArXiv.

Automated detection of circulating tumor cells with naive Bayesian classifiers

Jörg Lücke, C. Svensson, S. Krusekopf, 2014, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

The ELBO of Variational Autoencoders Converges to a Sum of Entropies

Asja Fischer, Zhenwen Dai, Jörg Lücke, 2020, AISTATS.

The Evidence Lower Bound of Variational Autoencoders Converges to a Sum of Three Entropies pdf

Jörg Lücke, Dennis Forster, Zhenwen Dai, 2020, ArXiv.

Closed-Form Entropy Limits - A Tool to Monitor Likelihood Optimization of Probabilistic Generative Models

Jörg Lücke, Marc Henniges, Jörg Lücke, 2012, AISTATS.

Invariant Face Recognitionin a Network of Cortical Columns

Jörg Lücke, Christoph von der Malsburg, Philipp Wolfrum, 2008, VISAPP.

A Variational EM Acceleration for Efficient Clustering at Very Large Scales

Jörg Lücke, F. Hirschberger, D. Forster, 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents

Jörg Lücke, Jakob Drefs, E. Guiraud, 2022 .

A Dynamical Model for Receptive Field Self-organization in V1 Cortical Columns

Jörg Lücke, Jörg Lücke, 2007, ICANN.

Unsupervised learning of translation invariant occlusive components

Zhenwen Dai, Jörg Lücke, Zhenwen Dai, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Speaker tracking for hearing aids

Steven van de Par, Jörg Lücke, Joachim Thiemann, 2016, 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP).