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ORCIDTomasz Danel
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2020 – today
- 2024
[j5]Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel M. Morkisz, Stanislaw Jastrzebski:
Relative molecule self-attention transformer. J. Cheminformatics 16(1): 3 (2024)- [j4]Lukasz Struski
, Michal Sadowski, Tomasz Danel, Jacek Tabor, Igor T. Podolak:
Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12068-12082 (2024) - 2023
- [j3]Agnieszka Wojtuch, Tomasz Danel, Sabina Podlewska, Lukasz Maziarka:
Extended study on atomic featurization in graph neural networks for molecular property prediction. J. Cheminformatics 15(1): 81 (2023) - [j2]Tobiasz Cieplinski, Tomasz Danel, Sabina Podlewska, Stanislaw Jastrzebski:
Generative Models Should at Least Be Able to Design Molecules That Dock Well: A New Benchmark. J. Chem. Inf. Model. 63(11): 3238-3247 (2023) - [c7]Dawid Rymarczyk, Daniel Dobrowolski, Tomasz Danel:
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction. SDM 2023: 379-387 - [c6]Lukasz Struski, Tomasz Danel, Marek Smieja, Jacek Tabor, Bartosz Zielinski:
SONGs: Self-Organizing Neural Graphs. WACV 2023: 3837-3846 - [i9]Tomasz Danel, Jan Leski, Sabina Podlewska, Igor T. Podolak:
Docking-based generative approaches in the search for new drug candidates. CoRR abs/2312.13944 (2023) - 2022
- [c5]Piotr Gainski, Lukasz Maziarka, Tomasz Danel, Stanislaw Jastrzebski:
HuggingMolecules: An Open-Source Library for Transformer-Based Molecular Property Prediction (Student Abstract). AAAI 2022: 12949-12950 - [i8]Dawid Rymarczyk, Daniel Dobrowolski, Tomasz Danel:
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction. CoRR abs/2210.03745 (2022) - 2021
- [c4]Lukasz Maziarka, Tomasz Danel:
Multitask Learning Using BERT with Task-Embedded Attention. IJCNN 2021: 1-6 - [c3]Agnieszka Pocha, Tomasz Danel, Sabina Podlewska, Jacek Tabor, Lukasz Maziarka:
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction. IJCNN 2021: 1-8 - [i7]Lukasz Struski, Tomasz Danel, Marek Smieja, Jacek Tabor, Bartosz Zielinski:
SONG: Self-Organizing Neural Graphs. CoRR abs/2107.13214 (2021) - [i6]Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel M. Morkisz, Stanislaw Jastrzebski:
Relative Molecule Self-Attention Transformer. CoRR abs/2110.05841 (2021) - 2020
- [j1]Lukasz Maziarka, Agnieszka Pocha, Jan Kaczmarczyk, Krzysztof Rataj, Tomasz Danel, Michal Warchol:
Mol-CycleGAN: a generative model for molecular optimization. J. Cheminformatics 12(1): 2 (2020) - [c2]Tomasz Danel, Marek Smieja, Lukasz Struski, Przemyslaw Spurek, Lukasz Maziarka:
Processing of Incomplete Images by (Graph) Convolutional Neural Networks. ICONIP (2) 2020: 512-523 - [c1]Tomasz Danel, Przemyslaw Spurek, Jacek Tabor, Marek Smieja, Lukasz Struski, Agnieszka Slowik, Lukasz Maziarka:
Spatial Graph Convolutional Networks. ICONIP (5) 2020: 668-675 - [i5]Lukasz Maziarka, Tomasz Danel, Slawomir Mucha, Krzysztof Rataj, Jacek Tabor, Stanislaw Jastrzebski:
Molecule Attention Transformer. CoRR abs/2002.08264 (2020) - [i4]Tobiasz Cieplinski, Tomasz Danel, Sabina Podlewska, Stanislaw Jastrzebski:
We should at least be able to Design Molecules that Dock Well. CoRR abs/2006.16955 (2020) - [i3]Tomasz Danel, Marek Smieja, Lukasz Struski, Przemyslaw Spurek, Lukasz Maziarka:
Processing of incomplete images by (graph) convolutional neural networks. CoRR abs/2010.13914 (2020) - [i2]Agnieszka Pocha, Tomasz Danel, Lukasz Maziarka:
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction. CoRR abs/2012.04444 (2020)
2010 – 2019
- 2019
- [i1]Przemyslaw Spurek, Tomasz Danel, Jacek Tabor, Marek Smieja, Lukasz Struski, Agnieszka Slowik, Lukasz Maziarka:
Geometric Graph Convolutional Neural Networks. CoRR abs/1909.05310 (2019)
Coauthor Index
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last updated on 2024-09-21 23:36 CEST by the dblp team
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