Jakub M. Tomczak
Jakub M. Tomczak
Assistant Professor at Vrije Universiteit Amsterdam
Verified email at vu.nl - Homepage
Cited by
Cited by
VAE with a VampPrior
J Tomczak, M Welling
International Conference on Artificial Intelligence and Statistics, 1214-1223, 2018
Attention-based deep multiple instance learning
M Ilse, JM Tomczak, M Welling
arXiv preprint arXiv:1802.04712, 2018
Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction
M Zięba, SK Tomczak, JM Tomczak
Expert systems with applications 58, 93-101, 2016
Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients
M Zięba, JM Tomczak, M Lubicz, J Świątek
Applied soft computing 14, 99-108, 2014
Hyperspherical variational auto-encoders
TR Davidson, L Falorsi, N De Cao, T Kipf, JM Tomczak
arXiv preprint arXiv:1804.00891, 2018
Sylvester Normalizing Flows for Variational Inference
R Berg, L Hasenclever, JM Tomczak, M Welling
arXiv preprint arXiv:1803.05649, 2018
Improving variational auto-encoders using householder flow
JM Tomczak, M Welling
arXiv preprint arXiv:1611.09630, 2016
Classification restricted Boltzmann machine for comprehensible credit scoring model
JM Tomczak, M Zięba
Expert Systems with Applications 42 (4), 1789-1796, 2015
Student courses recommendation using ant colony optimization
J Sobecki, JM Tomczak
Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence …, 2010
Interaction prediction in structure-based virtual screening using deep learning
A Gonczarek, JM Tomczak, S Zaręba, J Kaczmar, P Dąbrowski, ...
Computers in biology and medicine 100, 253-258, 2018
Decision rules extraction from data stream in the presence of changing context for diabetes treatment
JM Tomczak, A Gonczarek
Knowledge and Information Systems 34 (3), 521-546, 2013
Video compression with rate-distortion autoencoders
A Habibian, T Rozendaal, JM Tomczak, TS Cohen
Proceedings of the IEEE International Conference on Computer Vision, 7033-7042, 2019
Boosted SVM with active learning strategy for imbalanced data
M Zięba, JM Tomczak
Soft Computing 19 (12), 3357-3368, 2015
Prediction of breast cancer recurrence using Classification Restricted Boltzmann Machine with Dropping
JM Tomczak
arXiv preprint arXiv:1308.6324, 2013
Combinatorial Bayesian Optimization using the Graph Cartesian Product
C Oh, J Tomczak, E Gavves, M Welling
Advances in Neural Information Processing Systems, 2914-2924, 2019
Probabilistic combination of classification rules and its application to medical diagnosis
JM Tomczak, M ZięBa
Machine Learning 101 (1-3), 105-135, 2015
Context change detection for resource allocation in service-oriented systems
P Rygielski, JM Tomczak
Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence …, 2011
Application of Classification Restricted Boltzmann Machine with discriminative and sparse learning to medical domains
JM Tomczak
International Conference on Innovative Trends in Science, Engineering and …, 2014
Learning invariant features using subspace restricted Boltzmann machine
JM Tomczak, A Gonczarek
Neural Processing Letters 45 (1), 173-182, 2017
Articulated tracking with manifold regularized particle filter
A Gonczarek, JM Tomczak
Machine Vision and Applications 27 (2), 275-286, 2016
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