Seuraa
Jakub M. Tomczak
Jakub M. Tomczak
Muut nimetJakub Tomczak
Associate professor at Eindhoven University of Technology
Vahvistettu sähköpostiosoite verkkotunnuksessa tue.nl - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Attention-based deep multiple instance learning
M Ilse, J Tomczak, M Welling
International conference on machine learning, 2127-2136, 2018
21892018
VAE with a VampPrior
J Tomczak, M Welling
International conference on artificial intelligence and statistics, 1214-1223, 2018
7702018
Hyperspherical variational auto-encoders
TR Davidson, L Falorsi, N De Cao, T Kipf, JM Tomczak
arXiv preprint arXiv:1804.00891, 2018
5142018
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
4962016
Sylvester Normalizing Flows for Variational Inference
R Berg, L Hasenclever, JM Tomczak, M Welling
arXiv preprint arXiv:1803.05649, 2018
2712018
Video compression with rate-distortion autoencoders
A Habibian, T Rozendaal, JM Tomczak, TS Cohen
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
2632019
Conditional channel gated networks for task-aware continual learning
D Abati, J Tomczak, T Blankevoort, S Calderara, R Cucchiara, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
2462020
Diva: Domain invariant variational autoencoders
M Ilse, JM Tomczak, C Louizos, M Welling
Medical Imaging with Deep Learning, 322-348, 2020
2432020
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
2092014
Improving variational auto-encoders using householder flow
JM Tomczak, M Welling
arXiv preprint arXiv:1611.09630, 2016
1792016
Why Deep Generative Modeling?
JM Tomczak
Deep Generative Modeling, 1-12, 2022
1492022
Ckconv: Continuous kernel convolution for sequential data
DW Romero, A Kuzina, EJ Bekkers, JM Tomczak, M Hoogendoorn
arXiv preprint arXiv:2102.02611, 2021
1462021
Identification of ebselen and its analogues as potent covalent inhibitors of papain-like protease from SARS-CoV-2
E Weglarz-Tomczak, JM Tomczak, M Talma, M Burda-Grabowska, ...
Scientific reports 11 (1), 3640, 2021
1312021
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
1242019
Classification restricted Boltzmann machine for comprehensible credit scoring model
JM Tomczak, M Zięba
Expert Systems with Applications 42 (4), 1789-1796, 2015
1212015
Attentive group equivariant convolutional networks
D Romero, E Bekkers, J Tomczak, M Hoogendoorn
International Conference on Machine Learning, 8188-8199, 2020
1012020
Flexconv: Continuous kernel convolutions with differentiable kernel sizes
DW Romero, RJ Bruintjes, JM Tomczak, EJ Bekkers, M Hoogendoorn, ...
arXiv preprint arXiv:2110.08059, 2021
992021
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
912018
Time efficiency in optimization with a bayesian-evolutionary algorithm
G Lan, JM Tomczak, DM Roijers, AE Eiben
Swarm and Evolutionary Computation 69, 100970, 2022
852022
Selecting data augmentation for simulating interventions
M Ilse, JM Tomczak, P Forré
International conference on machine learning, 4555-4562, 2021
752021
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Artikkelit 1–20