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Lukasz Maziarka
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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]Magdalena Proszewska
, Maciej Wolczyk
Multi-Label Conditional Generation From Pre-Trained Models. IEEE Trans. Pattern Anal. Mach. Intell. 46(9): 6185-6198 (2024) - [i15]Lukasz Kucinski, Witold Drzewakowski, Mateusz Olko, Piotr Kozakowski, Lukasz Maziarka, Marta Emilia Nowakowska, Lukasz Kaiser, Piotr Milos:
tsGT: Stochastic Time Series Modeling With Transformer. CoRR abs/2403.05713 (2024) - 2023
- [j3]Agnieszka Wojtuch, Tomasz Danel
Extended study on atomic featurization in graph neural networks for molecular property prediction. J. Cheminformatics 15(1): 81 (2023) - 2022
- [j2]Lukasz Maziarka
OneFlow: One-Class Flow for Anomaly Detection Based on a Minimal Volume Region. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 8508-8519 (2022) - [c11]Maciej Wolczyk, Magdalena Proszewska, Lukasz Maziarka, Maciej Zieba, Patryk Wielopolski, Rafal Kurczab, Marek Smieja:
PluGeN: Multi-Label Conditional Generation from Pre-trained Models. AAAI 2022: 8647-8656 - [c10]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 - [c9]Lukasz Maziarka
On the Relationship Between Disentanglement and Multi-task Learning. ECML/PKDD (1) 2022: 625-641 - 2021
- [c8]Lukasz Maziarka, Tomasz Danel
Multitask Learning Using BERT with Task-Embedded Attention. IJCNN 2021: 1-6 - [c7]Agnieszka Pocha, Tomasz Danel
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction. IJCNN 2021: 1-8 - [i14]Marcin Sendera, Marek Smieja, Lukasz Maziarka, Lukasz Struski, Przemyslaw Spurek, Jacek Tabor:
Flow-based SVDD for anomaly detection. CoRR abs/2108.04907 (2021) - [i13]Maciej Wolczyk, Magdalena Proszewska, Lukasz Maziarka, Maciej Zieba, Patryk Wielopolski, Rafal Kurczab, Marek Smieja:
PluGeN: Multi-Label Conditional Generation From Pre-Trained Models. CoRR abs/2109.09011 (2021) - [i12]Lukasz Maziarka, Aleksandra Nowak, Maciej Wolczyk, Andrzej Bedychaj:
On the relationship between disentanglement and multi-task learning. CoRR abs/2110.03498 (2021) - [i11]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
Mol-CycleGAN: a generative model for molecular optimization. J. Cheminformatics 12(1): 2 (2020) - [c6]Przemyslaw Spurek
Non-linear ICA Based on Cramer-Wold Metric. ICONIP (3) 2020: 294-305 - [c5]Tomasz Danel
Processing of Incomplete Images by (Graph) Convolutional Neural Networks. ICONIP (2) 2020: 512-523 - [c4]Tomasz Danel
Spatial Graph Convolutional Networks. ICONIP (5) 2020: 668-675 - [i10]Lukasz Maziarka, Tomasz Danel, Slawomir Mucha, Krzysztof Rataj, Jacek Tabor, Stanislaw Jastrzebski:
Molecule Attention Transformer. CoRR abs/2002.08264 (2020) - [i9]Lukasz Maziarka, Marek Smieja, Marcin Sendera, Lukasz Struski, Jacek Tabor, Przemyslaw Spurek:
Flow-based anomaly detection. CoRR abs/2010.03002 (2020) - [i8]Tomasz Danel, Marek Smieja, Lukasz Struski, Przemyslaw Spurek, Lukasz Maziarka:
Processing of incomplete images by (graph) convolutional neural networks. CoRR abs/2010.13914 (2020) - [i7]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
- [c3]Sylwester Klocek
Hypernetwork Functional Image Representation. ICANN (Workshop) 2019: 496-510 - [c2]Lukasz Maziarka, Agnieszka Pocha, Jan Kaczmarczyk, Krzysztof Rataj, Michal Warchol:
Mol-CycleGAN - A Generative Model for Molecular Optimization. ICANN (Workshop) 2019: 810-816 - [c1]Lukasz Maziarka, Marek Smieja, Aleksandra Nowak
Set Aggregation Network as a Trainable Pooling Layer. ICONIP (2) 2019: 419-431 - [i6]Lukasz Maziarka, Agnieszka Pocha, Jan Kaczmarczyk, Krzysztof Rataj, Michal Warchol:
Mol-CycleGAN - a generative model for molecular optimization. CoRR abs/1902.02119 (2019) - [i5]Bartosz Wójcik, Lukasz Maziarka, Jacek Tabor:
LOSSGRAD: automatic learning rate in gradient descent. CoRR abs/1902.07656 (2019) - [i4]Sylwester Klocek, Lukasz Maziarka, Maciej Wolczyk, Jacek Tabor, Marek Smieja, Jakub Nowak:
Multi-task hypernetworks. CoRR abs/1902.10404 (2019) - [i3]Przemyslaw Spurek, Aleksandra Nowak, Jacek Tabor, Lukasz Maziarka, Stanislaw Jastrzebski:
Non-linear ICA based on Cramer-Wold metric. CoRR abs/1903.00201 (2019) - [i2]Przemyslaw Spurek, Tomasz Danel, Jacek Tabor, Marek Smieja, Lukasz Struski, Agnieszka Slowik
Geometric Graph Convolutional Neural Networks. CoRR abs/1909.05310 (2019) - 2018
- [i1]Lukasz Maziarka, Marek Smieja, Aleksandra Nowak, Jacek Tabor, Lukasz Struski, Przemyslaw Spurek:
Deep processing of structured data. CoRR abs/1810.01868 (2018)
Coauthor Index
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