Hypernetwork functional image representation S Klocek, Ł Maziarka, M Wołczyk, J Tabor, J Nowak, M Śmieja International Conference on Artificial Neural Networks, 496-510, 2019 | 79 | 2019 |
Urban driver: Learning to drive from real-world demonstrations using policy gradients O Scheel, L Bergamini, M Wolczyk, B Osiński, P Ondruska Conference on Robot Learning, 718-728, 2022 | 64 | 2022 |
Continual world: A robotic benchmark for continual reinforcement learning M Wołczyk, M Zając, R Pascanu, Ł Kuciński, P Miłoś Advances in Neural Information Processing Systems 34, 28496-28510, 2021 | 61 | 2021 |
Safetynet: Safe planning for real-world self-driving vehicles using machine-learned policies M Vitelli, Y Chang, Y Ye, A Ferreira, M Wołczyk, B Osiński, M Niendorf, ... 2022 International Conference on Robotics and Automation (ICRA), 897-904, 2022 | 47 | 2022 |
Zero time waste: Recycling predictions in early exit neural networks M Wołczyk, B Wójcik, K Bałazy, IT Podolak, J Tabor, M Śmieja, T Trzcinski Advances in Neural Information Processing Systems 34, 2516-2528, 2021 | 32 | 2021 |
Segma: Semi-supervised Gaussian mixture autoencoder M Śmieja, M Wołczyk, J Tabor, BC Geiger IEEE transactions on neural networks and learning systems 32 (9), 3930-3941, 2020 | 21 | 2020 |
Disentangling transfer in continual reinforcement learning M Wolczyk, M Zając, R Pascanu, Ł Kuciński, P Miłoś Advances in Neural Information Processing Systems 35, 6304-6317, 2022 | 20 | 2022 |
Continual learning with guarantees via weight interval constraints M Wołczyk, K Piczak, B Wójcik, L Pustelnik, P Morawiecki, J Tabor, ... International Conference on Machine Learning, 23897-23911, 2022 | 4 | 2022 |
Plugen: Multi-label conditional generation from pre-trained models M Wołczyk, M Proszewska, Ł Maziarka, M Zieba, P Wielopolski, ... Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8647-8656, 2022 | 3 | 2022 |
Biologically-inspired spatial neural networks M Wołczyk, J Tabor, M Śmieja, S Maszke arXiv preprint arXiv:1910.02776, 2019 | 3 | 2019 |
Zero time waste in pre-trained early exit neural networks B Wójcik, M Przewiȩźlikowski, F Szatkowski, M Wołczyk, K Bałazy, ... Neural Networks 168, 580-601, 2023 | 2 | 2023 |
On the relationship between disentanglement and multi-task learning Ł Maziarka, A Nowak, M Wołczyk, A Bedychaj Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 2 | 2022 |
Remember more by recalling less: Investigating the role of batch size in continual learning with experience replay (student abstract) M Wołczyk, A Krutsylo Proceedings of the AAAI Conference on Artificial Intelligence 35 (18), 15923 …, 2021 | 2 | 2021 |
Deep learning-based initialization for object packing M Wołczyk Schedae Informaticae 27, 2018 | 2 | 2018 |
Discovering modular solutions that generalize compositionally S Schug, S Kobayashi, Y Akram, M Wołczyk, A Proca, J Von Oswald, ... arXiv preprint arXiv:2312.15001, 2023 | 1 | 2023 |
The Role of Forgetting in Fine-Tuning Reinforcement Learning Models M Wolczyk, B Cupiał, M Ostaszewski, M Bortkiewicz, M Zając, R Pascanu, ... | 1 | 2023 |
Finding the optimal network depth in classification tasks B Wójcik, M Wołczyk, K Bałazy, J Tabor Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021 | 1 | 2021 |
AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale A Pardyl, M Wronka, M Wołczyk, K Adamczewski, T Trzciński, B Zieliński arXiv preprint arXiv:2404.03482, 2024 | | 2024 |
Multi-Label Conditional Generation From Pre-Trained Models M Proszewska, M Wołczyk, M Zieba, P Wielopolski, Ł Maziarka, M Śmieja IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | | 2024 |
Adaptiveness in Deep Learning Models M Wołczyk | | 2024 |