Katedra Uczenia Maszynowego - lista publikacji
Nadjednostka:
1-35 z 35.
2021
35.
Wojciech Masarczyk , Kamil Deja, Tomasz Trzciński
On robustness of generative representations against catastrophic forgetting, (2021), "Neural Information Processing : 28th International Conference, ICONIP 2021 : Sanur, Bali, Indonesia, December 8-12, 2021 : proceedings, part IV", Springer
34.
Ivona Tautkute , Tomasz Trzciński
SynthTriplet GAN : synthetic query expansion formultimodal retrieval, (2021), "Neural Information Processing : 28th International Conference, ICONIP 2021 : Sanur, Bali, Indonesia, December 8-12, 2021 : proceedings, part IV", Springer
33.
Arkadiusz Drabicki, Rafał Kucharski, Cats Oded
Mitigating bus bunching with real-time crowding information, Transportation vol. 2022 (2021), 28
32.
Zięba Maciej , Przemysław Spurek, Jacek Tabor, Tomasz Trzciński
31.
Łukasz Lepak, Robert Nowak, Karol Piczak, Kacper Radzikowski
30.
Adversarial Examples Detection and Analysis with Layer-wise Autoencoders, International Conference on Tools with Artificial Intelligence [ICTAI], (2021), 1322-1326
29.
Missing Glow Phenomenon: learning disentangled representation of missing data, International Conference on Neural Information Processing [ICONIP] vol. vol 1516 (2021), 196-204
28.
Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Przemysław Spurek, Tomasz Trzciński, Zięba Maciej
Non-Gaussian Gaussian Processes for Few-Shot Regression, Advances in Neural Information Processing Systems [NeurIPS](MAIN) vol. 34 (2021), 10285-10298
27.
Łukasz Kuciński, Piotr Miłoś, Razvan Pascanu, Maciej Wołczyk, Michał Zając
Continual World: A Robotic Benchmark For Continual Reinforcement Learning, Advances in Neural Information Processing Systems [NeurIPS](MAIN), (2021),
26.
Klaudia Bałazy, Igor Podolak, Marek Śmieja, Jacek Tabor, Tomasz Trzciński, Maciej Wołczyk, Bartosz Wójcik
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks, Advances in Neural Information Processing Systems [NeurIPS](MAIN) vol. 34 (2021), 1-13
25.
Łukasz Borchmann, Jurkiewicz Dawid, Filip Graliński, Michał Pietruszka, Tomasz Stanisławek, Karolina Szyndler, Michał Turski
DUE: End-to-End Document Understanding Benchmark, Advances in Neural Information Processing Systems [NeurIPS], (2021),
24.
Dawid Warszycki, Łukasz Struski, Marek Śmieja, Rafał Kafel, Rafał Kurczab
23.
Kacper Łasocha, Elżbieta Richter-Wąs, Michał Sadowski, Zbigniew Wąs
22.
Karol Piczak, Michał Sadowski, Przemysław Spurek, Tomasz Trzciński
Continual Learning of 3D Point Cloud Generators, International Conference on Neural Information Processing [ICONIP] vol. vol 13108 (2021), 330-341
21.
Rafał Jankowski, Sabina Podlewska, Agnieszka Wojtuch
How can SHAP values shape the metabolic stability?, Journal of Cheminformatics vol. 13 (2021), Article number: 74
20.
Andrzej Bojarski, Rafał Kurczab, Stefan Mordalski, Igor Podolak, Agnieszka Wojtuch
2D SIFt: a matrix of ligand-receptor interactions, Journal of Cheminformatics vol. 13 (2021), Article number: 66
19.
Karl Aberer, Klaudia Bałazy, Mohammadreza Banaei, Rémi Lebret, Jacek Tabor
Direction is what you need: Improving Word Embedding Compression in Large Language Models, Proceedings of the 6th Workshop On Representation Learning for Nlp (repl4nlp-2021) (2021), 322–330
18.
Jakub Chłędowski, Carlos Fernandez-Granda, Krzysztof J. Geras, Kangning Liu, Nan Wu, Shen Yiqiu
Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis, Proceedings of Machine Learning Research (2021),
17.
The Slow-Coloring Game on Sparse Graphs: k-Degenerate, Planar, and Outerplanar, Journal of Combinatorics vol. 12 (2021) (2021), 283 – 302
16.
Adriana Borowa, Anna Bracha, Maurycy Chronowski, Wojciech Ozimek, Dawid Rymarczyk, Bartosz Zieliński
Comparison of Supervised and Self-supervised Deep Representations Trained on Histological Image, World Congress on Medical and Health Informatics [MEDINFO] vol. Studies in Health Technology and Informatics 290 (2021), 1052-1053
15.
Łukasz Borchmann, Jurkiewicz Dawid, Tomasz Dwojak, Pałka Gabriela, Michał Pietruszka, Powalski Rafał
Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer, IEEE International Conference on Document Analysis and Recognition [ICDAR], (2021),
14.
Bartosz Bohaterewicz, Adrian Chrobak, Dominika Dudek, Magdalena Fafrowicz, Tadeusz Marek, Dagmara Mętel, Igor Podolak, Marcin Siwek, Anna Sobczak, Bartosz Wójcik
13.
Jakub Chłędowski, Adam Polak, Bartosz Szabucki, Konrad Żołna
Robust Learning-Augmented Caching: An Experimental Study, International Conference on Machine Learning [ICML], (2021), 1920-1930
12.
Ella Barkan, Sardius Chen, Jakub Chłędowski, Linda Du, Sushma Gaddam, Krzysztof J. Geras, Flora Gilboa-Solomon, Julia Goldberg, Pablo Gómez del Campo, Sana Hava, Laura Heacock, Daniel Khapun, Eric Kim, Jiyon Lee, Alana Lewin, Robert Martí, Alexandra Millet, Linda Moy, Sindhoora Murthy, Ujas Parikh, Jungkyu Park, Shalin Patel, Anastasia Plaunova, Kristine Pysarenko, Vadim Ratner, Beatriu Reig, Michal Rosen-Zvi, Yoel Shoshan, Melanie Wegener, Jan Witowski, Stacey Wolfson, Aviad Zlotnick
Lessons from the first DBTex Challenge, vol. 3 (2021), 735–736
11.
Tomasz Danel, Agnieszka Galanty, Igor Podolak, Irma Podolak, Michał Węgrzyn
10.
Tomasz Danel, Piotr Gaiński, Stanisław Jastrzębski, Łukasz Maziarka
HuggingMolecules: an open-source library for transformer-based molecular property prediction, International Conference On Learning Representations (workshop Track) (2021),
9.
Tomasz Danel, Łukasz Maziarka
Multitask Learning Using BERT with Task-Embedded Attention, IEEE International Joint Conference on Neural Networks [IJCNN], (2021),
8.
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction, IEEE International Joint Conference on Neural Networks [IJCNN], (2021), 1-8
7.
ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification, ACM International Conference on Knowledge Discovery and Data Mining [KDD](MAIN) vol. 9781450383325 (2021), 1420-1430
6.
Dominika Basaj, Michał Górszczak, Witold Oleszkiewicz, Barbara Rychalska, Igor Sieradzki, Tomasz Trzcinski, Bartosz Zieliński
Explaining Self-Supervised Image Representations with Visual Probing, International Joint Conference on Artificial Intelligence [IJCAI](MAIN), (2021), 592-598
5.
Deep learning classification of bacteria clones explained by persistence homology, IEEE International Joint Conference on Neural Networks [IJCNN] vol. 978-1-6654-3900-8 (2021), 1-8
4.
Kamil Deja, Jan Dubiński, Piotr Nowak, Przemysław Spurek, Tomasz Trzciński, Sandro Wenzel
End-to-End Sinkhorn Autoencoder With Noise Generator, IEEE Access vol. 9 (2021), 7211-7219
3.
Kernel Self-Attention for Weakly-supervised Image Classification using Deep Multiple Instance Learning, IEEE Workshop on Applications of Computer Vision [WACV] vol. 978-1-6654-0477-8 (2021), 1720-1729
2.
Łukasz Borchmann, Filip Graliński, Michał Pietruszka
Successive Halving Top-k Operator, National Conference of the American Association for Artificial Intelligence [AAAI], (2021),
1.
SeGMA: Semi-Supervised Gaussian Mixture Autoencoder, IEEE Transactions on Neural Networks and Learning Systems vol. 32/9 (2021), 3930-3941