Najnowsze publikacje

• Michał Zając, Tinne Tuytelaars, Gido van de Ven, Prediction Error-based Classification for Class-Incremental Learning, International Conference on Learning Representations [ICLR], (2024),
• Mateusz Olko, Michał Zając, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Łukasz Kuciński, Piotr Miłoś, Trust Your ∇: Gradient-based Intervention Targeting for Causal Discovery, Advances in Neural Information Processing Systems [NeurIPS](MAIN), (2023),
• Maciej Wołczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś, Disentangling Transfer in Continual Reinforcement Learning, Advances in Neural Information Processing Systems [NeurIPS](MAIN), (2022),
• Łukasz Kuciński, Piotr Miłoś, Razvan Pascanu, Maciej Wołczyk, Michał Zając, Continual World: A Robotic Benchmark For Continual Reinforcement Learning, Advances in Neural Information Processing Systems [NeurIPS](MAIN), (2021),
• Grzegorz Gutowski, Tomasz Krawczyk, Krzysztof Maziarz, Douglas West, Xuding Zhu, Michał Zając, The Slow-Coloring Game on Sparse Graphs: k-Degenerate, Planar, and Outerplanar, Journal of Combinatorics 12 (2021) (2021), 283 – 302