| Reinforcement learning for optimization of variational quantum circuit architectures M Ostaszewski, LM Trenkwalder, W Masarczyk, E Scerri, V Dunjko Advances in Neural Information Processing Systems 34, 18182-18194, 2021 | 158 | 2021 |
| Automatic pigment identification from hyperspectral data B Grabowski, W Masarczyk, P Głomb, A Mendys Journal of Cultural Heritage 31, 1-12, 2018 | 101 | 2018 |
| Reducing catastrophic forgetting with learning on synthetic data W Masarczyk, I Tautkute Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 46 | 2020 |
| Effective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling W Masarczyk, P Głomb, B Grabowski, M Ostaszewski Remote Sensing 12 (16), 2653, 2020 | 28* | 2020 |
| The tunnel effect: Building data representations in deep neural networks W Masarczyk, M Ostaszewski, E Imani, R Pascanu, P Miłoś, T Trzcinski Advances in Neural Information Processing Systems 36, 76772-76805, 2023 | 18 | 2023 |
| Binplay: A binary latent autoencoder for generative replay continual learning K Deja, P Wawrzyński, D Marczak, W Masarczyk, T Trzciński 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 11 | 2021 |
| Logarithmic Continual Learning W Masarczyk, P Wawrzyński, D Marczak, K Deja, T Trzciński IEEE Access 10, 117001-117010, 2022 | 5 | 2022 |
| On robustness of generative representations against catastrophic forgetting W Masarczyk, K Deja, T Trzcinski International Conference on Neural Information Processing, 325-333, 2021 | 5 | 2021 |
| Multiband VAE: latent space alignment for knowledge consolidation in continual learning K Deja, P Wawrzynski, W Masarczyk, D Marczak, T Trzciński Vienna: International Joint Conferences on Artificial Intelligence Organization, 2022 | 4 | 2022 |
| Reinforcement learning with experience replay and adaptation of action dispersion P Wawrzyński, W Masarczyk, M Ostaszewski arXiv preprint arXiv:2208.00156, 2022 | 1 | 2022 |
| Curriculum reinforcement learning for optimization of variational quantum circuit architectures M Ostaszewski, W Masarczyk, LM Trenkwalder, E Scerri, V Dunjko NeurIPS 2020, Third Workshop on Machine Learning and the Physical Sciences, 2020 | 1 | 2020 |
| On consequences of finetuning on data with highly discriminative features W Masarczyk, T Trzciński, M Ostaszewski arXiv preprint arXiv:2310.19537, 2023 | | 2023 |
Mateusz OstaszewskiWarsaw University of Technologyכתובת אימייל מאומתת בדומיין pw.edu.pl