| Mol-CycleGAN: a generative model for molecular optimization Ł Maziarka, A Pocha, J Kaczmarczyk, K Rataj, T Danel, M Warchoł Journal of Cheminformatics 12 (1), 1-18, 2020 | 276 | 2020 |
| Molecule Attention Transformer Ł Maziarka, T Danel, S Mucha, K Rataj, J Tabor, S Jastrzębski Neural Information Processing Systems (NeurIPS 2019 - Workshop track), 2020 | 206* | 2020 |
| Spatial Graph Convolutional Networks T Danel, P Spurek, J Tabor, M Śmieja, Ł Struski, A Słowik, Ł Maziarka International Conference on Neural Information Processing (ICONIP 2020 …, 2019 | 110* | 2019 |
| Hypernetwork functional image representation S Klocek, Ł Maziarka, M Wołczyk, J Tabor, J Nowak, M Śmieja International Conference on Artificial Neural Networks (ICANN 2019), 2019 | 89 | 2019 |
| Relative Molecule Self-Attention Transformer Ł Maziarka, D Majchrowski, T Danel, P Gaiński, J Tabor, I Podolak, ... Journal of Cheminformatics 16 (1), 3, 2021 | 27 | 2021 |
| Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction A Pocha, T Danel, S Podlewska, J Tabor, Ł Maziarka International Joint Conference on Neural Networks (IJCNN 2021); Neural …, 2020 | 8 | 2020 |
| OneFlow: One-class flow for anomaly detection based on a minimal volume region Ł Maziarka, M Smieja, M Sendera, Ł Struski, J Tabor, P Spurek IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 6* | 2021 |
| Non-linear ICA based on Cramer-Wold metric P Spurek, A Nowak, J Tabor, Ł Maziarka, S Jastrzębski International Conference on Neural Information Processing (ICONIP 2020), 2019 | 6 | 2019 |
| LOSSGRAD: automatic learning rate in gradient descent B Wójcik, Ł Maziarka, J Tabor International Conference on Theoretical Foundations of Machine Learning …, 2019 | 6 | 2019 |
| Extended study on atomic featurization in graph neural networks for molecular property prediction A Wojtuch, T Danel, S Podlewska, Ł Maziarka Journal of Cheminformatics 15 (1), 81, 2023 | 5 | 2023 |
| Plugen: Multi-label conditional generation from pre-trained models M Wołczyk, M Proszewska, Ł Maziarka, M Zieba, P Wielopolski, ... Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8647-8656, 2022 | 5 | 2022 |
| Processing of incomplete images by (graph) convolutional neural networks T Danel, M Śmieja, Ł Struski, P Spurek, L Maziarka International Conference on Machine Learning (ICML 2020 - Workshop track …, 2020 | 5 | 2020 |
| Multitask learning using BERT with task-embedded attention Ł Maziarka, T Danel 2021 International Joint Conference on Neural Networks (IJCNN), 1-6, 2021 | 4 | 2021 |
| Huggingmolecules: An open-source library for transformer-based molecular property prediction (student abstract) P Gaiński, Ł Maziarka, T Danel, S Jastrzebski Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 12949 …, 2022 | 3 | 2022 |
| On the relationship between disentanglement and multi-task learning Ł Maziarka, A Nowak, M Wołczyk, A Bedychaj European Conference on Machine Learning (ECMLPKDD 2022), 2021 | 3 | 2021 |
| Set Aggregation Network as a Trainable Pooling Layer Ł Maziarka, M Smieja, A Nowak, J Tabor, Ł Struski, P Spurek International Conference on Neural Information Processing (ICONIP 2019), 2019 | 3* | 2019 |
| De Novo Drug Design with a Docking Score Proxy T Danel, M Szymczak, Ł Maziarka, I Podolak, J Tabor, S Jastrzębski Machine Learning for Molecules Workshop at NeurIPS 2020, 2020 | 2 | 2020 |
| Multi-Label Conditional Generation From Pre-Trained Models M Proszewska, M Wołczyk, M Zieba, P Wielopolski, Ł Maziarka, M Śmieja IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | | 2024 |
| : Stochastic Time Series Modeling With Transformer Ł Kuciński, W Drzewakowski, M Olko, P Kozakowski, Ł Maziarka, ... arXiv preprint arXiv:2403.05713, 2024 | | 2024 |
| Stochastyczne Równania Różniczkowe Wstecz-teoria, zastosowania, symulacje Ł Maziarka | | 2020 |
Tomasz DanelJagiellonian UniversityVerified email at uj.edu.pl
