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Maciej Wolczyk
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2020 – today
- 2024
- [j3]Magdalena Proszewska, Maciej Wolczyk, Maciej Zieba, Patryk Wielopolski, Lukasz Maziarka, Marek Smieja:
Multi-Label Conditional Generation From Pre-Trained Models. IEEE Trans. Pattern Anal. Mach. Intell. 46(9): 6185-6198 (2024) - [c15]Simon Schug, Seijin Kobayashi, Yassir Akram, Maciej Wolczyk, Alexandra Proca, Johannes von Oswald, Razvan Pascanu, João Sacramento, Angelika Steger:
Discovering modular solutions that generalize compositionally. ICLR 2024 - [c14]Maciej Wolczyk, Bartlomiej Cupial, Mateusz Ostaszewski, Michal Bortkiewicz, Michal Zajac, Razvan Pascanu, Lukasz Kucinski, Piotr Milos:
Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem. ICML 2024 - [i17]Maciej Wolczyk, Bartlomiej Cupial, Mateusz Ostaszewski, Michal Bortkiewicz, Michal Zajac, Razvan Pascanu, Lukasz Kucinski, Piotr Milos:
Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem. CoRR abs/2402.02868 (2024) - [i16]Adam Pardyl, Michal Wronka, Maciej Wolczyk, Kamil Adamczewski, Tomasz Trzcinski, Bartosz Zielinski:
AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale. CoRR abs/2404.03482 (2024) - [i15]Maciej Pióro, Maciej Wolczyk, Razvan Pascanu, Johannes von Oswald, João Sacramento:
State Soup: In-Context Skill Learning, Retrieval and Mixing. CoRR abs/2406.08423 (2024) - 2023
- [j2]Bartosz Wójcik, Marcin Przewiezlikowski, Filip Szatkowski, Maciej Wolczyk, Klaudia Balazy, Bartlomiej Krzepkowski, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski:
Zero time waste in pre-trained early exit neural networks. Neural Networks 168: 580-601 (2023) - [c13]Samuel Kessler, Mateusz Ostaszewski, Michal Pawel Bortkiewicz, Mateusz Zarski, Maciej Wolczyk, Jack Parker-Holder, Stephen J. Roberts, Piotr Milos:
The Effectiveness of World Models for Continual Reinforcement Learning. CoLLAs 2023: 184-204 - [c12]Pawel Morawiecki, Andrii Krutsylo, Maciej Wolczyk, Marek Smieja:
Hebbian Continual Representation Learning. HICSS 2023: 1259-1268 - [i14]Simon Schug, Seijin Kobayashi, Yassir Akram, Maciej Wolczyk, Alexandra Proca, Johannes von Oswald, Razvan Pascanu, João Sacramento, Angelika Steger:
Discovering modular solutions that generalize compositionally. CoRR abs/2312.15001 (2023) - 2022
- [c11]Maciej Wolczyk, Magdalena Proszewska, Lukasz Maziarka, Maciej Zieba, Patryk Wielopolski, Rafal Kurczab, Marek Smieja:
PluGeN: Multi-Label Conditional Generation from Pre-trained Models. AAAI 2022: 8647-8656 - [c10]Maciej Wolczyk, Karol J. Piczak, Bartosz Wójcik, Lukasz Pustelnik, Pawel Morawiecki, Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek:
Continual Learning with Guarantees via Weight Interval Constraints. ICML 2022: 23897-23911 - [c9]Matt Vitelli, Yan Chang, Yawei Ye, Ana Ferreira, Maciej Wolczyk, Blazej Osinski, Moritz Niendorf, Hugo Grimmett, Qiangui Huang, Ashesh Jain, Peter Ondruska:
SafetyNet: Safe Planning for Real-World Self-Driving Vehicles Using Machine-Learned Policies. ICRA 2022: 897-904 - [c8]Maciej Wolczyk, Michal Zajac, Razvan Pascanu, Lukasz Kucinski, Piotr Milos:
Disentangling Transfer in Continual Reinforcement Learning. NeurIPS 2022 - [c7]Lukasz Maziarka, Aleksandra Nowak, Maciej Wolczyk, Andrzej Bedychaj:
On the Relationship Between Disentanglement and Multi-task Learning. ECML/PKDD (1) 2022: 625-641 - [i13]Maciej Wolczyk, Karol J. Piczak, Bartosz Wójcik, Lukasz Pustelnik, Pawel Morawiecki, Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek:
Continual Learning with Guarantees via Weight Interval Constraints. CoRR abs/2206.07996 (2022) - [i12]Pawel Morawiecki, Andrii Krutsylo, Maciej Wolczyk, Marek Smieja:
Hebbian Continual Representation Learning. CoRR abs/2207.04874 (2022) - [i11]Maciej Wolczyk, Michal Zajac, Razvan Pascanu, Lukasz Kucinski, Piotr Milos:
Disentangling Transfer in Continual Reinforcement Learning. CoRR abs/2209.13900 (2022) - 2021
- [j1]Marek Smieja, Maciej Wolczyk, Jacek Tabor, Bernhard C. Geiger:
SeGMA: Semi-Supervised Gaussian Mixture Autoencoder. IEEE Trans. Neural Networks Learn. Syst. 32(9): 3930-3941 (2021) - [c6]Maciej Wolczyk, Andrii Krutsylo:
Remember More by Recalling Less: Investigating the Role of Batch Size in Continual Learning with Experience Replay (Student Abstract). AAAI 2021: 15923-15924 - [c5]Oliver Scheel, Luca Bergamini, Maciej Wolczyk, Blazej Osinski, Peter Ondruska:
Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients. CoRL 2021: 718-728 - [c4]Maciej Wolczyk, Bartosz Wójcik, Klaudia Balazy, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski:
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. NeurIPS 2021: 2516-2528 - [c3]Maciej Wolczyk, Michal Zajac, Razvan Pascanu, Lukasz Kucinski, Piotr Milos:
Continual World: A Robotic Benchmark For Continual Reinforcement Learning. NeurIPS 2021: 28496-28510 - [i10]Maciej Wolczyk, Michal Zajac, Razvan Pascanu, Lukasz Kucinski, Piotr Milos:
Continual World: A Robotic Benchmark For Continual Reinforcement Learning. CoRR abs/2105.10919 (2021) - [i9]Maciej Wolczyk, Bartosz Wójcik, Klaudia Balazy, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski:
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. CoRR abs/2106.05409 (2021) - [i8]Maciej Wolczyk, Magdalena Proszewska, Lukasz Maziarka, Maciej Zieba, Patryk Wielopolski, Rafal Kurczab, Marek Smieja:
PluGeN: Multi-Label Conditional Generation From Pre-Trained Models. CoRR abs/2109.09011 (2021) - [i7]Oliver Scheel, Luca Bergamini, Maciej Wolczyk, Blazej Osinski, Peter Ondruska:
Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients. CoRR abs/2109.13333 (2021) - [i6]Matt Vitelli, Yan Chang, Yawei Ye, Maciej Wolczyk, Blazej Osinski, Moritz Niendorf, Hugo Grimmett, Qiangui Huang, Ashesh Jain, Peter Ondruska:
SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policies. CoRR abs/2109.13602 (2021) - [i5]Lukasz Maziarka, Aleksandra Nowak, Maciej Wolczyk, Andrzej Bedychaj:
On the relationship between disentanglement and multi-task learning. CoRR abs/2110.03498 (2021) - 2020
- [c2]Bartosz Wójcik, Maciej Wolczyk, Klaudia Balazy, Jacek Tabor:
Finding the Optimal Network Depth in Classification Tasks. ECML/PKDD (3) 2020: 263-278 - [i4]Bartosz Wójcik, Maciej Wolczyk, Klaudia Balazy, Jacek Tabor:
Finding the Optimal Network Depth in Classification Tasks. CoRR abs/2004.08172 (2020)
2010 – 2019
- 2019
- [c1]Sylwester Klocek, Lukasz Maziarka, Maciej Wolczyk, Jacek Tabor, Jakub Nowak, Marek Smieja:
Hypernetwork Functional Image Representation. ICANN (Workshop) 2019: 496-510 - [i3]Sylwester Klocek, Lukasz Maziarka, Maciej Wolczyk, Jacek Tabor, Marek Smieja, Jakub Nowak:
Multi-task hypernetworks. CoRR abs/1902.10404 (2019) - [i2]Marek Smieja, Maciej Wolczyk, Jacek Tabor, Bernhard C. Geiger:
SeGMA: Semi-Supervised Gaussian Mixture Auto-Encoder. CoRR abs/1906.09333 (2019) - [i1]Maciej Wolczyk, Jacek Tabor, Marek Smieja, Szymon Maszke:
Biologically-Inspired Spatial Neural Networks. CoRR abs/1910.02776 (2019)
Coauthor Index
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last updated on 2024-10-07 22:09 CEST by the dblp team
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