| 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 | 183 | 2020 |
| Molecule Attention Transformer Ł Maziarka, T Danel, S Mucha, K Rataj, J Tabor, S Jastrzębski arXiv preprint arXiv:2002.08264, 2020 | 137 | 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, 668-675, 2020 | 63* | 2020 |
| Generative Models Should at Least Be Able to Design Molecules That Dock Well: A New Benchmark T Ciepliński, T Danel, S Podlewska, S Jastrzȩbski Journal of Chemical Information and Modeling, 2023 | 33* | 2023 |
| Relative Molecule Self-Attention Transformer Ł Maziarka, D Majchrowski, T Danel, P Gaiński, J Tabor, I Podolak, ... arXiv preprint arXiv:2110.05841, 2021 | 11 | 2021 |
| Docking-based generative approaches in the search for new drug candidates T Danel, J Łęski, S Podlewska, IT Podolak Drug Discovery Today, 103439, 2022 | 9 | 2022 |
| Comparison of atom representations in graph neural networks for molecular property prediction A Pocha, T Danel, S Podlewska, J Tabor, Ł Maziarka 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 7 | 2021 |
| Deep convolutional neural network for preliminary in-field classification of lichen species A Galanty, T Danel, M Węgrzyn, I Podolak, I Podolak Biosystems Engineering 204, 15-25, 2021 | 5 | 2021 |
| Molecule-augmented attention transformer Ł Maziarka, T Danel, S Mucha, K Rataj, J Tabor, S Jastrzębski Workshop on Graph Representation Learning, Neural Information Processing Systems, 2019 | 4 | 2019 |
| Processing of incomplete images by (graph) convolutional neural networks T Danel, M Śmieja, Ł Struski, P Spurek, Ł Maziarka International Conference on Neural Information Processing, 512-523, 2020 | 3 | 2020 |
| Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models Ł Struski, M Sadowski, T Danel, J Tabor, IT Podolak IEEE Transactions on Neural Networks and Learning Systems, 2023 | 2 | 2023 |
| SONGs: Self-Organizing Neural Graphs Ł Struski, T Danel, M Śmieja, J Tabor, B Zieliński Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 2 | 2023 |
| Multitask Learning Using BERT with Task-Embedded Attention Ł Maziarka, T Danel 2021 International Joint Conference on Neural Networks (IJCNN), 1-6, 2021 | 2 | 2021 |
| ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction D Rymarczyk, D Dobrowolski, T Danel Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 1 | 2023 |
| Generation of new inhibitors of selected cytochrome P450 subtypes–In silico study T Danel, A Wojtuch, S Podlewska Computational and Structural Biotechnology Journal 20, 5639-5651, 2022 | 1 | 2022 |
| 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 | 1 | 2020 |
| 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 | | 2022 |
| Deep convolutional neural networks on mobile devices T Danel Faculty of Mathematics and Computer Science, Jagiellonian University, 2018 | | 2018 |
Łukasz MaziarkaJagiellonian University & BrainlyZweryfikowany adres z student.uj.edu.pl
