Model-based reinforcement learning for atari L Kaiser, M Babaeizadeh, P Milos, B Osinski, RH Campbell, ...
arXiv preprint arXiv:1903.00374, 2019
1033 2019 Uncertainty-sensitive learning and planning with ensembles P Miłoś, Ł Kuciński, K Czechowski, P Kozakowski, M Klimek
arXiv preprint arXiv:1912.09996, 2019
8 2019 Q-value weighted regression: Reinforcement learning with limited data P Kozakowski, L Kaiser, H Michalewski, A Mohiuddin, K Kańska
2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022
5 2022 Planning and learning using adaptive entropy tree search P Kozakowski, M Pacek, P Miloś
2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022
3 2022 Molecule-edit templates for efficient and accurate retrosynthesis prediction M Sacha, M Sadowski, P Kozakowski, R van Workum, S Jastrzębski
arXiv preprint arXiv:2310.07313, 2023
2 2023 Structure and randomness in planning and reinforcement learning K Czechowski, P Januszewski, P Kozakowski, Ł Kuciński, P Miłoś
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
2 2021 : Stochastic Time Series Modeling With TransformerŁ Kuciński, W Drzewakowski, M Olko, P Kozakowski, Ł Maziarka, ...
arXiv preprint arXiv:2403.05713, 2024
2024 tsGT: Stochastic Time Series Modeling With Transformer L Kucinski, W Drzewakowski, M Olko, P Kozakowski, L Maziarka, ...
CoRR, 2024
2024 RL: Generic reinforcement learning codebase in TensorFlow BM Li, A Cowen-Rivers, P Kozakowski, D Tao, SR Kamalakara, ...
Journal of Open Source Software 4 (42), 1524, 2019
2019 Forecasting Deep Learning Dynamics with Applications to Hyperparameter Tuning P Kozakowski, Ł Kaiser, A Mohiuddin