J. Lampinen

Jouko Lampinen, Aki Vehtari, Simo Särkkä, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Rao-Blackwellized particle filter for multiple target tracking

Jouko Lampinen, Aki Vehtari, Simo Särkkä, 2007, Inf. Fusion.

Sequential Monte Carlo for Bayesian matching of objects with occlusions

Jouko Lampinen, Toni Tamminen, J. Lampinen, 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A Bayesian Occlusion Model for Sequential Object Matching

Jouko Lampinen, Toni Tamminen, J. Lampinen, 2004, BMVC.

Neural Network Systems, Techniques and Applications in Pattern Recognition

E. Oja, Jorma T. Laaksonen, J. Lampinen, 1997 .

Jouko Lampinen, Mikko Sams, Juha M. Lahnakoski, 2012, PloS one.

On steerability of Gabor-type filters for feature detection

Jouko Lampinen, Ilkka Kalliomäki, J. Lampinen, 2007, Pattern Recognit. Lett..

Advances in Neural Network Modeling

Jouko Lampinen, J. Lampinen, 1997 .

Time series prediction by Kalman smoother with cross-validated noise density

Jouko Lampinen, Aki Vehtari, Simo Särkkä, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

A PRECISION EXPERIMENT ON ELECTRONS, PHOTONS AND MUONS AT LHC

Y. L. Zhao, John Man-shun Ma, E. Oja, 1993 .

Cam shape optimisation by genetic algorithm

Jouko Lampinen, J. Lampinen, 2003, Comput. Aided Des..

Probabilistic methods in multiple target tracking - Review and bibliography

Jouko Lampinen, Aki Vehtari, Simo Särkkä, 2004 .

Building Spatial Choice Models from Aggregate Data

Jouko Lampinen, J. Lampinen, Tommi Orpana, 2003 .

Molecular dynamics simulation of the structure and melting transition of the Si(001) surface

K. Kaski, J. Lampinen, R. Nieminen, 1988 .

Object Classification and Recognition From Mobile Laser Scanning Point Clouds in a Road Environment

Jouko Lampinen, Juha Hyyppä, Anttoni Jaakkola, 2016, IEEE Transactions on Geoscience and Remote Sensing.

Bayesian approach for neural networks--review and case studies

Jouko Lampinen, Aki Vehtari, Aki Vehtari, 2001, Neural Networks.

Hierarchical Bayesian estimates of distributed MEG sources: Theoretical aspects and comparison of variational and MCMC methods

Jouko Lampinen, Aki Vehtari, Mikko Sams, 2007, NeuroImage.

Self-Organizing Feature Extraction in Recognition of Wood Surface Defects and Color Images

Jouko Lampinen, Seppo Smolander, J. Lampinen, 1996, Int. J. Pattern Recognit. Artif. Intell..

Model selection via predictive explanatory power

Jouko Lampinen, Aki Vehtari, J. Lampinen, 2004 .

Joint Modeling of Facial Expression and Shape from Video

Jouko Lampinen, Jari Kätsyri, Michael Frydrych, 2005, SCIA.

Clustering properties of hierarchical self-organizing maps

Jouko Lampinen, Erkki Oja, E. Oja, 1992, Journal of Mathematical Imaging and Vision.

Bayesian Input Variable Selection Using Posterior Probabilities and Expected Utilities

Jouko Lampinen, Aki Vehtari, Aki Vehtari, 2002 .

Bayesian MLP neural networks for image analysis

Jouko Lampinen, Aki Vehtari, Aki Vehtari, 2000, Pattern Recognit. Lett..

Automatic relevance determination based hierarchical Bayesian MEG inversion in practice

Jouko Lampinen, Aki Vehtari, Mikko Sams, 2007, NeuroImage.

Bayesian analysis of the neuromagnetic inverse problem with ℓ p -norm priors

Jouko Lampinen, Aki Vehtari, Mikko Sams, 2005, NeuroImage.

Reproducibility of importance extraction methods in neural network based fMRI classification

Jouko Lampinen, Mikko Sams, Iiro P. Jääskeläinen, 2017, NeuroImage.

Application of Bayesian neural network in electrical impedance tomography

Jouko Lampinen, Aki Vehtari, Kimmo Leinonen, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Digital-image-based tree measurement for forest inventory

Jouko Lampinen, Jukka Heikkonen, Jouni Juujarvi, 1998, Other Conferences.

Learning an Object Model for Feature Matching in Clutter

Jouko Lampinen, Toni Tamminen, J. Lampinen, 2003, SCIA.

Hidden sources of joy, fear, and sadness: Explicit versus implicit neural processing of musical emotions

M. Sams, J. Numminen, E. Brattico, 2016, Neuropsychologia.

Discrete Neural Signatures of Basic Emotions.

R. Hari, M. Sams, P. Vuilleumier, 2016, Cerebral cortex.

Two-Stage Processing of Sounds Explains Behavioral Performance Variations due to Changes in Stimulus Contrast and Selective Attention: An MEG Study

M. Sams, A. Nummenmaa, I. Jääskeläinen, 2012, PloS one.

On the generative probability density model in the self-organizing map

Jouko Lampinen, Timo Kostiainen, J. Lampinen, 2002, Neurocomputing.

On Bayesian Model Asessment and Choice Using Cross-Validation Predictive Densities

Jouko Lampinen, Aki Vehtari, J. Lampinen, 2001 .

Incremental Object Matching with Bayesian Methods and Particle Filters

Jouko Lampinen, Miika Toivanen, J. Lampinen, 2009, 2009 Digital Image Computing: Techniques and Applications.

Incremental Bayesian learning of feature points from natural images

Jouko Lampinen, Miika Toivanen, J. Lampinen, 2009, 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

Bayesian Input Variable Selection Using Cross-Validation Predictive Densities and Reversible Jump MCMC

J. Lampinen, A. Vehtari, Aki Vehtari, 2001 .

Modeling of Pose Effects in Oriented Filter Responses for Head Pose Estimation

Jouko Lampinen, Ilkka Kalliomäki, J. Lampinen, 2003, SCIA.

Bayesian inverse analysis of neuromagnetic data using cortically constrained multiple dipoles

Jouko Lampinen, Aki Vehtari, Mikko Sams, 2007, Human brain mapping.

Molecular dynamics simulation of epitaxial growth of the Si(001) surface

K. Kaski, J. Lampinen, R. Nieminen, 1988 .

Reproducibility of importance extraction methods in neural network

L. Nummenmaa, I. Jääskeläinen, J. Lampinen, 2022 .