| Combating noisy labels in object detection datasets K Chachuła, J Łyskawa, B Olber, P Frątczak, A Popowicz, K Radlak arXiv preprint arXiv:2211.13993, 2022 | 5 | 2022 |
| A framework for reinforcement learning with autocorrelated actions M Szulc, J Łyskawa, P Wawrzyński Neural Information Processing: 27th International Conference, ICONIP 2020 …, 2020 | 3 | 2020 |
| ACERAC: efficient reinforcement learning in fine time discretization J Łyskawa, P Wawrzyński IEEE Transactions on Neural Networks and Learning Systems 35 (2), 2719-2731, 2022 | 2 | 2022 |
| Subgoal Reachability in Goal Conditioned Hierarchical Reinforcement Learning M Bortkiewicz, J Łyskawa, P Wawrzyński, M Ostaszewski, A Grudkowski, ... 16th International Conference on Agents and Artificial Intelligence, 2024 | 1 | 2024 |
| Influence of IQT on research in ICT B Bednarski, Ł Lepak, J Łyskawa, P Pieńczuk, M Rosoł, R Romaniuk International Journal of Electronics and Telecommunications 68 (2), 2022 | 1 | 2022 |
| Actor-Critic with variable time discretization via sustained actions J Łyskawa, P Wawrzyński International Conference on Neural Information Processing, 476-489, 2023 | | 2023 |
| Detecting Out-of-Distribution Objects Using Neuron Activation Patterns B Olber, K Radlak, K Chachuła, J Łyskawa, P Frątczak ECAI 2023, 1803-1810, 2023 | | 2023 |
| Emergency action termination for immediate reaction in hierarchical reinforcement learning M Bortkiewicz, J Łyskawa, P Wawrzyński, M Ostaszewski, A Grudkowski, ... arXiv preprint arXiv:2211.06351, 2022 | | 2022 |
| Implementation of ASD+ M algorithm in TensorFlow JJ Łyskawa Instytut Informatyki, 2019 | | 2019 |
