Katedra Uczenia Maszynowego - lista publikacji

1-200 z 313.

2025

312.
Bartosz Zieliński, Adam Pardyl, Grzegorz Kurzejamski, Jan Olszewski, Tomasz Trzciński
Beyond Grids: Exploring Elastic Input Sampling for Vision Transformers, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2025),

2024

311.
Modelling the Rise and Fall of Two-sided Markets, International Joint Conference on Autonomous Agents and Multiagent Systems [AAMAS](MAIN), (2024), 679-687
309.
Krzysztof Misztal, Ewelina Złotkowska, Anna Wlazło, Małgorzata Kiełkiewicz, Paulina Dziosa, Krzysztof Soja, Anna Barczak-Brzyżek, Marcin Filipecki
307.
Zięba Maciej , Marcin Przewięźlikowski, Marek Śmieja, Jacek Tabor, Tomasz Trzciński, Przemysław Spurek
RegFlow: Probabilistic Flow-Based Regression for Future Prediction, Asian Conference on Intelligent Information and Database Systems [ACIIDS], (2024), 267–279
306.
Andrzej Bedychaj, Jacek Tabor, Marek Śmieja
StyleAutoEncoder for manipulating image attributes using pre-trained StyleGAN, Pacific-Asia Conference on Knowledge Discovery and Data Mining [PAKDD], (2024), 118-130
305.
Jordy Van Landeghem, Ruben Tito, Łukasz Borchmann, Michał Pietruszka, Jurkiewicz Dawid, Powalski Rafał , Paweł Józiak, Sanket Biswas, Mickael Coustaty, Tomasz Stanisławek
ICDAR 2023 competition on document understanding of everything (DUDE), IEEE International Conference on Document Analysis and Recognition [ICDAR], (2024),
304.
Michał Pietruszka, Michał Turski, Łukasz Borchmann, Tomasz Dwojak, Pałka Gabriela, Karolina Szyndler, Jurkiewicz Dawid, Łukasz Garncarek
STable: Table Generation Framework for Encoder-Decoder Models, European Association of Computational Linguistics [EACL](MAIN), (2024), 2454–2472
303.
Przemysław Spurek, Marcin Przewięźlikowski, Jacek Tabor, Zięba Maciej , Przemysław Przybysz
302.
Przemysław Spurek, Tomasz Trzciński, Joanna Waczyńska, Dominik Zimny
301.
Przemysław Spurek, Wojciech Zając, Piotr Borycki, Joanna Waczyńska, Jacek Tabor, Zięba Maciej
NeRFlame: Flame-Based Conditioning of NeRF for 3D Face Rendering, International Conference on Computational Science [ICCS](MAIN) vol. 14832 (2024), 346--361
300.
Bartosz Zieliński, Adam Pardyl, Michał Wronka, Maciej Wołczyk, Kamil Adamczewski, Tomasz Trzciński
AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale, European Conference on Computer Vision [ECCV], (2024),
299.
Bartosz Zieliński, Marcin Przewięźlikowski, Marcin Osial, Marek Śmieja
A deep cut into Split Federated Self-Supervised Learning, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD](MAIN), (2024), 444-459
296.
Przemysław Spurek, Sebastian Winczowski, Zięba Maciej , Tomasz Trzcinski, Kacper Kania, Marcin Mazur
Modeling 3D Surfaces with a Locally Conditioned Atlas, International Conference on Computational Science [ICCS](MAIN) vol. 14833 (2024), 100-115
292.
Łukasz Struski, Paweł Morkisz, Przemysław Spurek, Samuel Rodriguez Bernabeu, Tomasz Trzciński
291.
Michał Zając, Tinne Tuytelaars, Gido van de Ven
Prediction Error-based Classification for Class-Incremental Learning, International Conference on Learning Representations [ICLR], (2024),
289.
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations, National Conference of the American Association for Artificial Intelligence [AAAI](MAIN) vol. 38 (19) (2024), 21563 - 21573
288.
Adrian Suwała, Bartosz Wójcik, Magdalena Proszewska, Jacek Tabor, Przemysław Spurek, Marek Śmieja
Face Identity-Aware Disentanglement in StyleGAN, IEEE Workshop on Applications of Computer Vision [WACV], (2024), 10
287.
Magdalena Proszewska, Marcin Mazur, Tomasz Trzcinski, Przemysław Spurek
HyperCube: Implicit Field Representations of Voxelized 3D Models (Student Abstract), National Conference of the American Association for Artificial Intelligence [AAAI] vol. 38 (2024), 23623-23625

2023

284.
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
281.
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),
280.
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),
279.
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
278.
Tobiasz Ciepliński, Tomasz Danel, Sabina Podlewska, Stanisław Jastrzębski
276.
Bartosz Wójcik, Marcin Przewięźlikowski, Filip Szatkowski, Maciej Wołczyk, Klaudia Bałazy, Bartłomiej Krzepkowski, Igor Podolak, Jacek Tabor, Marek Śmieja, Tomasz Trzciński
275.
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
274.
ProPML: Probability Partial Multi-label Learning, IEEE International Conference on Data Science and Advanced Analytics [DSAA], (2023), 1-8
273.
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
272.
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
271.
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
270.
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
269.
Mohammadreza Banaei, Klaudia Bałazy, Artur Kasymov, Rémi Lebret, Jacek Tabor, Karl Aberer
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
268.
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
267.
Tomasz Danel, Jan Łęski, Sabina Podlewska, Igor Podolak
266.
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
265.
Przemysław Spurek, Marcin Sendera, Marcin Przewięźlikowski, Jan Miksa, Mateusz Rajski, Konrad Karanowski, Maciej Zieba, Jacek Tabor
264.
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
263.
Michał Znaleźniak, Przemysław Rola, Patryk Kaszuba, Jacek Tabor, Marek Śmieja
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
262.
Krzysztof Misztal, Mirosław Szwed, Witold Żukowski, Rafał Kozłowski
261.
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
260.
Bounding Evidence and Estimating Log-Likelihood in VAE, International Conference on Artificial Intelligence and Statistics [AISTATS](MAIN) vol. 206 (2023), 5036-5051
259.
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
258.
Bartosz Zieliński, Witold Oleszkiewicz, Dominika Basaj, Igor Sieradzki, Michał Górszczak, Barbara Rychalska, Koryna Lewandowska, Tomasz Trzcinski
257.
Morawiecki Paweł, Andrii Krutsylo, Maciej Wołczyk, Marek Śmieja
Hebbian Continual Representation Learning, Hawaii International Conference on System Sciences [HICSS], (2023), 1259-1268
256.
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
255.
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts, IEEE Workshop on Applications of Computer Vision [WACV](MAIN) vol. 2023 (2023), 1481-1492
254.
SONGs: Self-Organizing Neural Graphs, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2023), 3837-3846

2022

252.
Romuald A. Janik, Igor Podolak, Łukasz Struski, Anna Ceglarek, Koryna Lewandowska, Barbara Sikora-Wachowicz, Tadeusz Marek, Magdalena Fąfrowicz
251.
Jarosław Żygierewicz, Romuald A. Janik, Igor Podolak, Alan Drozd, Urszula Malinowska, Martyna Poziomska, Jakub Wojciechowski, Paweł Ogniewski, Paweł Niedbalski, Iwona Terczyńska, Jacek Rogala
247.
Maciej Wołczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś
Disentangling Transfer in Continual Reinforcement Learning, Advances in Neural Information Processing Systems [NeurIPS](MAIN), (2022),
246.
Tomasz Trzciński, Kamil Deja, Paweł Wawrzynski , Wojciech Masarczyk , Daniel Marczak
Multiband VAE: latent space alignment for knowledge consolidation in continual learning, International Joint Conference on Artificial Intelligence [IJCAI](MAIN), (2022), 2902-2908
244.
Krzysztof Misztal, Anna Drożdż, Tomasz Kołodziej, Sonia Wróbel, Natalia Targosz-Korecka, Marek Drab, Robert jach, Carina Rząca, Magdalena Surman, Małgorzata Przybyło, Zenon Rajfur, Ewa Ł. Stępień
243.
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 (2022), 13–24
241.
Piotr Bartman-Szwarc, Jakub Banaśkiewicz, Szymon Drenda, Maciej Manna, Michael Olesik, Paweł Rozwoda, Michał Sadowski, Sylwester Arabas
240.
Przemysław Spurek, Artur Kasymov, Marcin Mazur, Diana Janik, Sławomir K. Tadeja, Łukasz Struski, Jacek Tabor, Tomasz Trzciński
HyperPocket: generative point cloud completion, IEEE/RSJ International Conference on Intelligent Robots and Systems [IROS], (2022), 6848-6853
239.
Batch size reconstruction-distribution trade-off in kernel based generative autoencoders, IEEE International Conference on Image Processing [ICIP], (2022), 3728-3732
238.
Piotr Gaiński, Łukasz Maziarka, Tomasz Danel, Stanisław Jastrzębski
HuggingMolecules: An Open-Source Library for Transformer-Based Molecular Property Prediction (Student Abstract), National Conference of the American Association for Artificial Intelligence [AAAI], (2022), 12949-12950
237.
On the relationship between disentanglement and multi-task learning, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD](MAIN), (2022),
236.
Nonlinear Weighted Independent Component Analysis, International Conference on Information Processing and Management of Uncertainty [IPMU] vol. II (2022), 3–16
234.
Przemysław Spurek, Jacek Tabor, Piotr Tempczyk, Rafał Michaluk, Łukasz Garncarek, Adam Golinski
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood, International Conference on Machine Learning [ICML](MAIN), (2022), 21205-21231
233.
Jacek Tabor, Maciej Wołczyk, Karol Piczak, Bartosz Wójcik, Łukasz Pustelnik, Morawiecki Paweł, Tomasz Trzcinski, Przemysław Spurek
Continual Learning with Guarantees via Weight Interval Constraints, International Conference on Machine Learning [ICML](MAIN), (2022), 23897-23911
232.
Dawid Rymarczyk, Łukasz Struski, Michał Górszczak, Koryna Lewandowska, Jacek Tabor, Bartosz Zieliński
Interpretable Image Classification with Differentiable Prototypes Assignment, European Conference on Computer Vision [ECCV](MAIN) vol. Lecture Notes in Computer Science 13672 (2022), 351-368
231.
Naumov Vitalii, Olha Shulika, Oleksandra Orda, Hanna Vasiutina, Marek Bauer, Myroslav Oliskevych
229.
Bartosz Zieliński, Dawid Rymarczyk, Aneta Kaczyńska, Jarosław Kraus, Adam Pardyl, Marek Skomorowski
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD](MAIN) vol. Lecture Notes in Computer Science 13713 (2022), 421-436
227.
Bernhard C. Geiger, Sophie Steger, Marek Śmieja
Semi-Supervised Clustering via Information-Theoretic Markov Chain Aggregation, ACM Symposium on Applied Computing [SAC](MAIN), (2022), 1136-1139
226.
Maciej Wołczyk, Magdalena Proszewska, Łukasz Maziarka, Zięba Maciej , Patryk Wielopolski, Rafał Kurczab, Marek Śmieja
PluGeN: Multi-Label Conditional Generation From Pre-Trained Models, National Conference of the American Association for Artificial Intelligence [AAAI](MAIN) vol. 36/8 (2022), 8647-8656
225.
Łukasz Borchmann, Łukasz Garncarek, Michał Pietruszka
Sparsifying Transformer Models with Trainable Representation Pooling, Association of Computational Linguistics [ACL](MAIN), (2022),
224.
Weakly-supervised cell classification for effective High Content Screening, International Conference on Computational Science [ICCS](MAIN) vol. Lecture Notes in Computer Science 13350 (2022), 318–330
223.
Dominika Basaj, Witold Oleszkiewicz, Tomasz Trzciński, Bartosz Zieliński
Which Visual Features Impact the Performance of Target Task in Self-supervised Learning?, International Conference on Computational Science [ICCS](MAIN) vol. Lecture Notes in Computer Science 13350 (2022), 331–344
219.
Marcin Przewięźlikowski, Marek Śmieja, Łukasz Struski, Jacek Tabor
MisConv: Convolutional Neural Networks for Missing Data, IEEE Workshop on Applications of Computer Vision [WACV], (2022), 2060-2069
218.
Łukasz Struski, Jacek Tabor, Szymon Bobek, Sławomir K. Tadeja, Przemysław Stachura, Timoleon Kipourus, Grzegorz Nalepa, Per Ola Kristensson

2021

216.
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
215.
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
214.
212.
Łukasz Lepak, Robert Nowak, Karol Piczak, Kacper Radzikowski
211.
Bartosz Wójcik, Morawiecki Paweł, Marek Śmieja, Tomasz Krzyżek, Przemysław Spurek, Jacek Tabor
Adversarial Examples Detection and Analysis with Layer-wise Autoencoders, International Conference on Tools with Artificial Intelligence [ICTAI], (2021), 1322-1326
210.
Missing Glow Phenomenon: learning disentangled representation of missing data, International Conference on Neural Information Processing [ICONIP] vol. vol 1516 (2021), 196-204
209.
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
208.
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),
207.
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks, Advances in Neural Information Processing Systems [NeurIPS](MAIN) vol. 34 (2021), 1-13
206.
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),
204.
203.
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
202.
Rafał Jankowski, Sabina Podlewska, Agnieszka Wojtuch
201.
Andrzej Bojarski, Rafał Kurczab, Stefan Mordalski, Igor Podolak, Agnieszka Wojtuch
200.
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
199.
Jakub Chłędowski, Carlos Fernandez-Granda, Krzysztof J. Geras, Kangning Liu, Nan Wu, Shen Yiqiu
198.
Grzegorz Gutowski, Tomasz Krawczyk, Krzysztof Maziarz, Douglas West, Xuding Zhu, Michał Zając
197.
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
196.
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),
195.
Bartosz Bohaterewicz, Adrian Chrobak, Dominika Dudek, Magdalena Fafrowicz, Tadeusz Marek, Dagmara Mętel, Igor Podolak, Marcin Siwek, Anna Sobczak, Bartosz Wójcik
194.
Jakub Chłędowski, Adam Polak, Bartosz Szabucki, Konrad Żołna
Robust Learning-Augmented Caching: An Experimental Study, International Conference on Machine Learning [ICML], (2021), 1920-1930
193.
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
192.
Tomasz Danel, Agnieszka Galanty, Igor Podolak, Irma Podolak, Michał Węgrzyn
191.
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),
190.
Tomasz Danel, Łukasz Maziarka
Multitask Learning Using BERT with Task-Embedded Attention, IEEE International Joint Conference on Neural Networks [IJCNN], (2021),
189.
Tomasz Danel, Łukasz Maziarka, Sabina Podlewska, Jacek Tabor, Agnieszka Wojtuch
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction, IEEE International Joint Conference on Neural Networks [IJCNN], (2021), 1-8
188.
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
187.
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
186.
Adriana Borowa, Monika Brzychczy-Włoch, Dorota Ochońska, Dawid Rymarczyk, Bartosz Zieliński
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
185.
Kamil Deja, Jan Dubiński, Piotr Nowak, Przemysław Spurek, Tomasz Trzciński, Sandro Wenzel
184.
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
183.
Łukasz Borchmann, Filip Graliński, Michał Pietruszka
Successive Halving Top-k Operator, National Conference of the American Association for Artificial Intelligence [AAAI], (2021),

2020

181.
‪Gregory S. Duane, Witold Dzwinel, Marcin Sendera
Supermodeling: the next level of abstraction in the use of data assimilation, International Conference on Computational Science [ICCS] vol. vol. Lecture Notes in Computer Science book series (LNCS, vol. 12142) (2020), 133-147
180.
Andrzej Bojarski, Stanisław Jastrzębski, Stefan Mordalski, Sabina Podlewska, Maciej Szymczak, Jacek Tabor, Agnieszka Wojtuch
179.
Tomasz Konopczyński, Michał Koperski, Rafał Nowak, Piotr Semberecki, Tomasz Trzciński
Plugin Networks for Inference under Partial Evidence, IEEE Workshop on Applications of Computer Vision [WACV], (2020),
178.
177.
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models, European Symposium on Artificial Neural Networks [ESANN], (2020), 6
176.
Marcin Przewięźlikowski, Marek Śmieja, Łukasz Struski
Estimating conditional density of missing values using deep Gaussian mixture model, International Conference on Neural Information Processing [ICONIP] vol. Lecture Notes in Computer Science volume 12534 (2020), 220-231
175.
Marek Śmieja, Maciej Kołomycki, Łukasz Struski, Mateusz Juda, Mario A.T. Figueiredo
Iterative Imputation of Missing Data using Auto-encoder Dynamics, International Conference on Neural Information Processing [ICONIP] vol. Lecture Notes in Computer Science, volume 12534 (2020), 258-269
174.
Processing of Incomplete Images by (Graph) Convolutional Neural Networks, International Conference On Neural Information Processing vol. Lecture Notes in Computer Science, volume 12533 (2020), 512-523
173.
Spatial Graph Convolutional Networks, International Conference On Neural Information Processing vol. Communications in Computer and Information Science book series (CCIS, volume 1333) (2020), 668-675
172.
Non-linear ICA based on Cramer-Wold metric, International Conference On Neural Information Processing vol. Lecture Notes in Computer Science book series (LNCS, volume 12534) (2020),
171.
Krzysztof Galias, Silviu Homoceanu, Adam Jakubowski, Henryk Michalewski, Piotr Miłoś, Błażej Osiński, Paweł Zięcina
Simulation-Based Reinforcement Learning for Real-World Autonomous Driving, IEEE International Conference on Robotics and Automation [ICRA], (2020), 6411-6418
170.
Zięba Maciej , Przemysław Spurek, Jacek Tabor, Tomasz Trzciński, Sebastian Winczowski, Maciej Zamorski
Hypernetwork approach to generating point clouds, International Conference on Machine Learning [ICML](MAIN), (2020),
169.
Kyunghyun Cho, Krzysztof J. Geras, Konrad Żołna
168.
Yoshua Bengio, Leonard Boussioux, Maxime Chevalier-Boisvert, Bahdanau Dzmitry, David Yu-Tung Hui, Chitwan Saharia, Konrad Żołna
Combating False Negatives in Adversarial Imitation Learning, National Conference of the American Association for Artificial Intelligence [AAAI], (2020), 13999-14000
167.
Krzysztof Galias, Damian Stachura, Konrad Żołna
Leakage-Robust Classifier via Mask-Enhanced Training, National Conference of the American Association for Artificial Intelligence [AAAI], (2020), 13923-13924
166.
Marek Śmieja, Maciej Kołomycki, Łukasz Struski, Mateusz Juda, Mario A.T. Figueiredo
Can auto-encoders help with filling missing data?, International Conference On Learning Represenation (workshop Track) (2020), 6
165.
Marcin Przewięźlikowski, Marek Śmieja, Łukasz Struski
Estimating conditional density of missing values using deep Gaussian mixture model, International Conference On Machine Learning (workshop Track) (2020), 6
164.
Łukasz Borchmann, Jakub Chłędowski, Tomasz Dwojak, Filip Graliński, Michał Pietruszka
From Dataset Recycling to Multi-Property Extraction and Beyond, Conference on Computational Natural Language Learning [CoNLL] vol. Proceedings of the 24th Conference on Computational Natural Language Learning (2020),
163.
Finding the Optimal Network Depth in Classification Tasks, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (PKDD and ECML combined from 2008) [ECML PKDD], (2020),
162.
Devansh Arpit, Kyunghyun Cho, Stanislav Fort, Krzysztof J. Geras, Stanisław Jastrzębski, Maciej Szymczak, Jacek Tabor
The Break-Even Point on Optimization Trajectories of Deep Neural Networks, 8th International Conference On Learning Representations (2020),
161.
Andrzej Bojarski, Stanisław Jastrzębski, Stefan Mordalski, Sabina Podlewska, Maciej Szymczak, Jacek Tabor, Agnieszka Wojtuch
160.
Olivier Bachem, Olivier Bousquet, Lasse Espeholt, Sylvain Gelly, Karol Kurach, Marcin Michalski, Anton Raichuk, Carlos Riquelme, Piotr Stańczyk, Damien Vincent, Michał Zając
Google Research Football: A Novel Reinforcement Learning Environment, Proceedings of the Aaai Conference On Artificial Intelligence vol. Vol 34 No 04 (2020), 4501-4510
158.
Processing of incomplete images by (graph) convolutional neural networks, International Conference On Machine Learning (workshop Track) (2020),
157.
Flow-based SVDD for anomaly detection, International Conference On Machine Learning (workshop Track) (2020),
156.
Monika Brzychczy-Włoch, Adam Piekarczyk, Dawid Rymarczyk, Agnieszka Sroka-Oleksiak, Bartosz Zieliński
152.
Tomasz Danel, Jan Kaczmarczyk, Łukasz Maziarka, Krzysztof Rataj, Michał Warchoł, Agnieszka Wojtuch

2019

150.
Stanisław Jastrzębski, Maciej A. Nowak, Jacek Tabor, Wojciech Tarnowski, Piotr Warchoł
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function, International Conference on Artificial Intelligence and Statistics [AISTATS], (2019), 10
149.
Kyunghyun Cho, Krzysztof J. Geras, Konrad Żołna
Classifier-Agnostic Saliency Map Extraction, National Conference of the American Association for Artificial Intelligence [AAAI], (2019), 10087-10088
148.
Pedro Pinheiro, Negar Rostamzadeh, Michał Zając, Konrad Żołna
Adversarial framing for image and video classification, National Conference of the American Association for Artificial Intelligence [AAAI], (2019), 10077-10078
147.
Andrzej Bojarski, Stanisław Jastrzębski, Damian Leśniak, Sabina Podlewska, Igor Sieradzki, Jacek Tabor
144.
Arkadiusz Czekajski, Damian Leśniak, Igor Podolak, Adam Roman, Bartosz Zieliński
Variational Auto-Encoders for Generating Feature-Preserving Automata, Proceedings of Ncma 2019, Books@ocg.at (austrian Computer Society) (2019), 171-185
143.
Set Aggregation Network as a Trainable Pooling Layer, International Conference On Neural Information Processing vol. Lecture Notes in Computer Science book series (LNCS, volume 11954) (2019), 419-431
142.
Tomasz Danel, Stanisław Jastrzębski, Łukasz Maziarka, Sławomir Mucha, Krzysztof Rataj, Jacek Tabor
Molecule-Augmented Attention Transformer, Neural Information Processing Systems (workshop Track) (2019),
141.
Jan Kaczmarczyk, Łukasz Maziarka, Krzysztof Rataj, Michał Warchoł, Agnieszka Wojtuch
Mol-CycleGAN - A Generative Model for Molecular Optimization, Artificial Neural Networks and Machine Learning – Icann 2019: Workshop and Special Sessions (2019), 810-816
140.
Sylwester Klocek, Łukasz Maziarka, Jakub Nowak, Marek Śmieja, Jacek Tabor, Maciej Wołczyk
Hypernetwork Functional Image Representation, Artificial Neural Networks and Machine Learning – Icann 2019: Workshop and Special Sessions (2019), 496-510
139.
Damian Leśniak, Igor Podolak, Igor Sieradzki
Distribution-Interpolation Trade off in Generative Models, International Conference On Learning Representations (2019),
136.
Maciej Brzeski, Hubert Dryja, Paweł Gora, Karnas Katarzyna, Arkadiusz Klemenko, Adrian Kochański, Dawid Kopczyk, Magdalena Kukawska, Marcin Możejko, Przemysław Przybyszewski
Solving Traffic Signal Setting Problem Using Machine Learning, International Conference On Models and Technologies for Intelligent Transportation Systems (2019),

2018

131.
Bartosz Borucki, Beata Ciszkowska-Lyson, Norbert Kapiński, Krzysztof Nowiński, Tomasz Trzciński, Jakub Zieliński
Estimating Achilles tendon healing progress with convolutional neural networks, Medical Image Computing and Computer-Assisted Intervention [MICCAI], (2018),
130.
Yoshua Bengio, Laurent Charlin, Rosemary Ke, Zhouhan Lin, Christopher Pal, Joelle Pineau, Alessandro Sordoni, Adam Trischler, Konrad Żołna
Focused Hierarchical RNNs for Conditional Sequence Processing, International Conference on Machine Learning [ICML], (2018),
129.
Jakub Chłędowski, Stanisław Jastrzębski, Tomasz Wesołowski
128.
Pedro Pinheiro, Negar Rostamzadeh, Michał Zając, Konrad Żołna
126.
Andrzej Bojarski, Stanisław Jastrzębski, Damian Leśniak, Sabina Podlewska, Igor Sieradzki, Jacek Tabor
125.
On modeling objects using sequence of moment invariants, Lecture Notes in Computer Science (2018), 92-102
124.
Maciej Brzeski, Paweł Gora, Arkadiusz Klemenko, Adrian Kochański, Marcin Możejko
123.
Maciej Brzeski, Paweł Gora, Łukasz Mądry, Marcin Możejko, Łukasz Skowronek
118.
Processing of missing data by neural networks, Advances in Neural Information Processing Systems vol. 31 (2018), 2719-2729
117.
Feature Selection in Texts, Proceedings of the 10th International Conference On Computer Recognition Systems Cores 2017 vol. 578. Advances in Intelligent Systems and Computing (2018), 336-345