Jakub M. Tomczak
Vrije Universiteit Amsterdam
H-index: 28
Europe-Netherlands
Top articles of Jakub M. Tomczak
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
A-nesi: A scalable approximate method for probabilistic neurosymbolic inference | Advances in Neural Information Processing Systems | Emile van Krieken Thiviyan Thanapalasingam Jakub Tomczak Frank Van Harmelen Annette Ten Teije | 2024/2/13 |
Mixed Models with Multiple Instance Learning | Jan P Engelmann Alessandro Palma Jakub M Tomczak Fabian Theis Francesco Paolo Casale | 2024/4/18 | |
Variational Stochastic Gradient Descent for Deep Neural Networks | arXiv preprint arXiv:2404.06549 | Haotian Chen Anna Kuzina Babak Esmaeili Jakub M Tomczak | 2024/4/9 |
Discouraging posterior collapse in hierarchical Variational Autoencoders using context | arXiv preprint arXiv:2302.09976 | Anna Kuzina Jakub M Tomczak | 2023/2/20 |
De Novo Drug Design with Joint Transformers | arXiv preprint arXiv:2310.02066 | Adam Izdebski Ewelina Weglarz-Tomczak Ewa Szczurek Jakub M Tomczak | 2023/10/3 |
Modelling Long Range Dependencies in D: From Task-Specific to a General Purpose CNN | arXiv preprint arXiv:2301.10540 | David M Knigge David W Romero Albert Gu Efstratios Gavves Erik J Bekkers | 2023/1/25 |
Lamarck's Revenge: Inheritance of Learned Traits Can Make Robot Evolution Better | arXiv preprint arXiv:2309.13099 | Jie Luo Karine Miras Jakub Tomczak Agoston E Eiben | 2023/9/22 |
A comparison of controller architectures and learning mechanisms for arbitrary robot morphologies | Jie Luo Jakub Tomczak Karine Miras Agoston E Eiben | 2023/12/5 | |
Learning data representations with joint diffusion models | Kamil Deja Tomasz Trzciński Jakub M Tomczak | 2023/9/17 | |
Enhancing robot evolution through Lamarckian principles | Scientific Reports | Jie Luo Karine Miras Jakub Tomczak Agoston E Eiben | 2023/11/30 |
Continuous Kendall Shape Variational Autoencoders | Sharvaree Vadgama Jakub M Tomczak Erik Bekkers | 2023/8/1 | |
Device for and computer implemented method of digital signal processing | 2023/11/21 | ||
Exploring continual learning of diffusion models | arXiv preprint arXiv:2303.15342 | Michał Zając Kamil Deja Anna Kuzina Jakub M Tomczak Tomasz Trzciński | 2023/3/27 |
Attention-based Multi-instance Mixed Models | arXiv preprint arXiv:2311.02455 | Jan P Engelmann Alessandro Palma Jakub M Tomczak Fabian J Theis Francesco Paolo Casale | 2023/11/4 |
Towards a General Purpose CNN for Long Range Dependencies in D | arXiv preprint arXiv:2206.03398 | David W Romero David M Knigge Albert Gu Erik J Bekkers Efstratios Gavves | 2022/6/7 |
The effects of learning in morphologically evolving robot systems | Frontiers in Robotics and AI | Jie Luo Aart C Stuurman Jakub M Tomczak Jacintha Ellers Agoston E Eiben | 2022/5/27 |
Alleviating adversarial attacks on variational autoencoders with mcmc | Anna Kuzina Max Welling Jakub Mikolaj Tomczak | 2022 | |
Time efficiency in optimization with a bayesian-evolutionary algorithm | Swarm and Evolutionary Computation | Gongjin Lan Jakub M Tomczak Diederik M Roijers AE Eiben | 2022/3/1 |
Why Deep Generative Modeling? | Jakub M Tomczak | 2022 | |
On analyzing generative and denoising capabilities of diffusion-based deep generative models | Kamil Deja Anna Kuzina Tomasz Trzciński Jakub M Tomczak | 2022/5/31 |
Co-Authors
