Katedra Uczenia Maszynowego - lista publikacji
Nadjednostka:
1-36 z 36.
2023
36.
35.
Jordy Van Landeghem, Ruben Tito, Łukasz Borchmann, Michał Pietruszka, Paweł Józiak, Powalski Rafał , Jurkiewicz Dawid, Mickael Coustaty, Bertrand Ackaert, Ernest Valveny, Matthew Blaschko, Sien Moens, Tomasz Stanisławek
Document Understanding Dataset and Evaluation (DUDE), IEEE International Conference on Computer Vision [ICCV](MAIN), (2023), 19528-19540
34.
Rafał Kucharski, Arkadiusz Drabicki, Cats Oded , Szarata Andrzej
33.
Network structures of urban ride-pooling problems and their properties, Social Network Analysis and Mining vol. 13 (1) 89 (2023), 1-13
32.
Aleksandra Nowak, Bram Grooten, Decebal Constantin Mocanu , Jacek Tabor
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training, Advances in Neural Information Processing Systems [NeurIPS](MAIN), (2023),
31.
Mateusz Olko, Michał Zając, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Łukasz Kuciński, Piotr Miłoś
Trust Your ∇: Gradient-based Intervention Targeting for Causal Discovery, Advances in Neural Information Processing Systems [NeurIPS](MAIN), (2023),
30.
Witold Wydmański, Oleksii Bulenok, Marek Śmieja
HyperTab: Hypernetwork Approach for Deep Learning on Small Tabular Datasets, IEEE International Conference on Data Science and Advanced Analytics [DSAA], (2023), 9
29.
Tobiasz Ciepliński, Tomasz Danel, Sabina Podlewska, Stanisław Jastrzębski
28.
Agnieszka Wojtuch, Tomasz Danel, Sabina Podlewska, Łukasz Maziarka
27.
Bartosz Wójcik, Marcin Przewięźlikowski, Filip Szatkowski, Maciej Wołczyk, Klaudia Bałazy, Bartłomiej Krzepkowski, Igor Podolak, Jacek Tabor, Marek Śmieja, Tomasz Trzciński
Zero time waste in pre-trained early exit neural networks, Neural Networks vol. 168 (2023), 580-601
26.
Bartosz Zieliński, Dawid Rymarczyk, Weiwei Schultz, Adriana Borowa, Joshua Friedman, Tomasz Danel, Patrick Branigan, Michał Chałupczak, Anna Bracha, Tomasz Krawiec, Michał Warchoł, Katherine Li, Gert De Hertogh, Louis R. Ghanem, Aleksandar Stojmirovic
25.
ProPML: Probability Partial Multi-label Learning, IEEE International Conference on Data Science and Advanced Analytics [DSAA], (2023), 1-8
24.
Bartosz Zieliński, Łukasz Struski, Dawid Rymarczyk, Arkadiusz Lewicki, Robert Sabiniewicz, Jacek Tabor
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging, European Conference on Artificial Intelligence [ECAI] vol. 372 (2023), 2210 - 2217
23.
Bartosz Zieliński, Adam Pardyl, Dawid Rymarczyk, Joanna Jaworek-Korjakowska, Dariusz Kucharski, Andrzej Brodzicki, Julia Lasek, Zofia Schneider, Iwona Kucybała, Andrzej Urbanik, Rafał Obuchowicz, Zbisław Tabor
CompLung: Comprehensive Computer-Aided Diagnosis of Lung Cancer, European Conference on Artificial Intelligence [ECAI] vol. 372 (2023), 1835 - 1842
22.
Bartosz Zieliński, Dawid Rymarczyk, Joost van de Weijer , Bartłomiej Twardowski
ICICLE: Interpretable Class Incremental Continual Learning, IEEE International Conference on Computer Vision [ICCV](MAIN) vol. 2023 (2023), 1887-1898
21.
r-softmax: Generalized Softmax with Controllable Sparsity Rate, International Conference on Computational Science [ICCS] vol. Lecture Notes in Computer Science, vol 14074. Springer, Cham (2023), 137-145
20.
Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models, European Association of Computational Linguistics [EACL] vol. Findings of the Association for Computational Linguistics: EACL 2023 (2023), 1788–1805
19.
Step by Step Loss Goes Very Far: Multi-Step Quantization for Adversarial Text Attacks, European Association of Computational Linguistics [EACL] vol. Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics (2023), 2038–2048
18.
Tomasz Danel, Jan Łęski, Sabina Podlewska, Igor Podolak
Docking-based generative approaches in the search for new drug candidates, Drug Discovery Today vol. 28/2 (2023), 103439
17.
Przemysław Spurek, Karol Piczak, Jacek Tabor, Tomasz Trzciński, Filip Szatkowski
Hypernetworks build Implicit Neural Representations of Sounds, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD] vol. 14172 (2023), 661–676
16.
Przemysław Spurek, Marcin Sendera, Marcin Przewięźlikowski, Jan Miksa, Mateusz Rajski, Konrad Karanowski, Maciej Zieba, Jacek Tabor
15.
ChiENN: Embracing Molecular Chirality with Graph Neural Networks, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD] vol. Lecture Notes in Computer Science(), vol 14171. Springer, Cham (2023), 36-52
14.
Contrastive Hierarchical Clustering, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD] vol. Lecture Notes in Computer Science(), vol 14169. Springer, Cham. (2023), 627–643
13.
Krzysztof Misztal, Mirosław Szwed, Witold Żukowski, Rafał Kozłowski
High-Energy Transformations of Fossil Fuels in the Cement Industry, Energies vol. 16(9), 3634 (2023), 1-14
12.
Bartosz Zieliński, Adam Pardyl, Grzegorz Rypeść, Grzegorz Kurzejamski, Tomasz Trzciński
Active Visual Exploration Based on Attention-Map Entropy, International Joint Conference on Artificial Intelligence [IJCAI](MAIN), (2023), 1303-1311
11.
Bounding Evidence and Estimating Log-Likelihood in VAE, International Conference on Artificial Intelligence and Statistics [AISTATS](MAIN) vol. 206 (2023), 5036-5051
10.
Przemysław Spurek, Jacek Tabor, Marcin Sendera, Marcin Przewięźlikowski, Konrad Karanowski, Zięba Maciej
Hypershot: Few-shot learning by kernel hypernetworks, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2023), 2469--2478
9.
Bartosz Zieliński, Witold Oleszkiewicz, Dominika Basaj, Igor Sieradzki, Michał Górszczak, Barbara Rychalska, Koryna Lewandowska, Tomasz Trzcinski
Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations, IEEE Access vol. 11 (2023), 13028-13043
8.
Morawiecki Paweł, Andrii Krutsylo, Maciej Wołczyk, Marek Śmieja
Hebbian Continual Representation Learning, Hawaii International Conference on System Sciences [HICSS], (2023), 1259-1268
7.
Dawid Rymarczyk, Daniel Dobrowolski, Tomasz Danel
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction, SIAM International Conference on Data Mining [SDM] vol. 978-1-61197-765-3 (2023), 379 - 387
6.
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts, IEEE Workshop on Applications of Computer Vision [WACV](MAIN) vol. 2023 (2023), 1481-1492
5.
SONGs: Self-Organizing Neural Graphs, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2023), 3837-3846
4.
Przemysław Spurek, Przemysław Stachura, Ivan Kostiuk, Sławomir K. Tadeja, Tomasz Trzciński
3.
Maciej Wołczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś
Disentangling Transfer in Continual Reinforcement Learning, Advances in Neural Information Processing Systems [NeurIPS](MAIN), (2023), 6304-6317
2.
Automating Patient-Level Lung Cancer Diagnosis in Different Data Regimes, International Conference on Neural Information Processing [ICONIP](MAIN) vol. Communications in Computer and Information Science 1794 (2023), 13–24
1.
Bartosz Zieliński, Adriana Borowa, Dawid Rymarczyk, Dorota Ochońska, Agnieszka Sroka-Oleksiak, Monika Brzychczy-Włoch