Achievements

Topic People Info Year Kind
A deep cut into Split Federated Self-Supervised Learning Marcin Przewięźlikowski , Marcin Osial , Marek Śmieja , Bartosz Zieliński ECML PKDD 2024 paper
Sparser, Better, Deeper, Stronger: Improving Sparse Training with Exact Orthogonal Initialization Aleksandra Nowak , Łukasz Gniecki , Filip Szatkowski , Jacek Tabor ICML 2024 paper
Prediction Error-based Classification for Class-Incremental Learning Michał Zając , Tinne Tuytelaars , Gido M. van de Ven ICLR 2024 paper
Divide and not forget Ensemble of selectively trained experts in Continual Learning Grzegorz Rypeść , Sebastian Cygert , Valeriya Khan , Tomasz Trzcinski , Bartosz Zieliński , Bartłomiej Twardowski ICLR 2024 paper
Modelling the Rise and Fall of Two-Sided Mobility Markets with Microsimulation Farnoud Ghasemi , Rafał Kucharski AAMAS 2024 paper
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations Mikołaj Sacha , Bartosz Jura , Dawid Rymarczyk , Łukasz Struski , Jacek Tabor , Bartosz Zieliński AAAI 2024 paper
Meta-learning in Deep Neural Networks Jacek Tabor OPUS 25 2023 grant
Where to look next - guiding active visual exploration with internal model uncertainty Adam Pardyl PRELUDIUM 22 2023 grant
Improving the transferability of self-supervised learning models Marcin Przewięźlikowski PRELUDIUM 22 2023 grant
Computationally efficient dynamic neural networks Bartosz Wójcik PRELUDIUM 22 2023 grant
Deep generative models in image processing Szymon Knop 2023 PhD defense
Deep learning methods in pharmaceutical sciences Tomasz Danel 2023 PhD defense
Zero time waste in pre-trained early exit neural networks Bartosz Wójcik , Marcin Przewięźlikowski , Filip Szatkowski , Maciej Wołczyk , Klaudia Bałazy , Bartłomiej Krzepkowski , Igor Podolak , Jacek Tabor , Marek Śmieja , Tomasz Trzciński Neural Networks, vol. 168 2023 paper
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training Aleksandra Nowak , Bram Grooten , Decebal Constantin Mocanu , Jacek Tabor NeurIPS 2023 paper
Trust Your ∇: Gradient-based Intervention Targeting for Causal Discovery Mateusz Olko , Michał Zając , Aleksandra Nowak , Nino Scherrer , Yashas Annadani , Stefan Bauer , Łukasz Kuciński , Piotr Miłoś NeurIPS 2023 paper
Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders Jan Dubiński , Stanisław Pawlak , Franzisca Boenisch , Tomasz Trzciński , Adam Dziedzic NeurIPS 2023 paper
The Tunnel Effect: Building Data Representations in Deep Neural Networks Wojciech Masarczyk , Mateusz Ostaszewski , Ehsan Imani , Razvan Pascanu , Piotr Miłoś , Tomasz Trzciński NeurIPS 2023 paper
Document Understanding Dataset and Evaluation (DUDE) Jordy Van Landeghem , Rubén Tito , Łukasz Borchmann , Michał Pietruszka , Paweł Józiak , Rafał Powalski , Dawid Jurkiewicz , Mickaël Coustaty , Bertrand Ackaert , Ernest Valveny , Matthew Blaschko , Sien Moens , Tomasz Stanisławek ICCV 2023 paper
ICICLE: Interpretable Class Incremental Continual Learning Dawid Rymarczyk , Joost van de Weijer , Bartosz Zieliński , Bartłomiej Twardowski ICCV 2023 paper
CompLung: Comprehensive Computer-Aided Diagnosis of Lung Cancer Adam Pardyl , Dawid Rymarczyk , Joanna Jaworek-Korjakowska , Dariusz Kucharski , Andrzej Brodzicki , Julia Lasek , Zofia Schneider , Iwona Kucybała , Andrzej Urbanik , Rafał Obuchowicz , Zbisław Tabor , Bartosz Zieliński ECAI 2023 paper
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging Łukasz Struski , Dawid Rymarczyk , Arkadiusz Lewicki , Robert Sabiniewicz , Jacek Tabor , Bartosz Zieliński ECAI 2023 paper
Hypernetworks build Implicit Neural Representations of Sounds Filip Szatkowski , Karol Piczak , Przemyslaw Spurek , Jacek Tabor , Tomasz Trzcinski ECML 2023 paper
ChiENN: Embracing Molecular Chirality with Graph Neural Networks Piotr Gaiński , Michał Koziarski , Jacek Tabor , Marek Śmieja ECML 2023 paper
Contrastive Hierarchical Clustering Michał Znaleźniak , Przemysław Rola , Patryk Kaszuba , Jacek Tabor , Marek Śmieja ECML 2023 paper
Interpretowalne metody zrównoważonej sztucznej inteligencji tłumaczące decyzje w sposób intuicyjny Bartosz Zieliński OPUS 24 2023 grant
Active Visual Exploration Based on Attention-Map Entropy Adam Pardyl , Grzegorz Rypeść , Grzegorz Kurzejamski , Bartosz Zieliński , Tomasz Trzciński IJCAI 2023 paper
Sieci prototypowe jako krok do interpretowalnej analizy funkcji białek Witold Wydmański Perły Nauki 2023 2023 grant
Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models Mohammadreza Banaei , Klaudia Bałazy , Artur Kasymov , Remi Lebret , Jacek Tabor , Karl Aberer EACL 2023 paper
Step by Step Loss Goes Very Far: Multi-Step Quantization for Adversarial Text Attacks Piotr Gaiński , Klaudia Bałazy EACL 2023 paper
ProGReST: Prototypical Graph Regression Soft Trees for Molecular Property Prediction Dawid Rymarczyk , Daniel Dobrowolski , Tomasz Danel SDM 2023 paper
Conditional deep generative models Marek Śmieja OPUS 23 2022 grant
Balancing priors in Bayesian Neural Networks Tomasz Kuśmierczyk POLONEZ BIS 2 2022 grant
Improving interpretability in deep neural networks Dawid Rymarczyk PRELUDIUM 21 2022 grant
Better adaptation in Meta-Learning Marcin Sendera PRELUDIUM 21 2022 grant
COeXISTENCE between humans and machines in urban mobility Rafał Kucharski ERC Starting Grant 2022 grant
Sparsifying Transformer Models with Trainable Representation Pooling Michał Pietruszka , Łukasz Borchmann , Łukasz Garncarek ACL (Spotlight) 2022 paper
SONGs: Self-Organizing Neural Graphs Łukasz Struski , Tomasz Danel , Marek Śmieja , Jacek Tabor , Bartosz Zieliński WACV 2023 paper
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts Mikołaj Sacha , Dawid Rymarczyk , Łukasz Struski , Jacek Tabor , Bartosz Zieliński WACV 2023 paper
HyperShot: Few-Shot Learning by Kernel HyperNetworks Marcin Sendera , Marcin Przewięźlikowski , Konrad Karanowski , Maciej Zięba , Jacek Tabor , Przemysław Spurek WACV 2023 paper
Discovering wiring patterns influencing neural network performance Aleksandra Nowak , Romuald Janik ECML PKDD 2022 paper
On the relationship between disentanglement and multi-task learning Łukasz Maziarka , Aleksandra Nowak , Maciej Wołczyk , Andrzej Bedychaj ECML PKDD 2022 paper
Multimodal and reinforcement learning platform for personalizing cancer management Krzysztof Geras ARTIQ - AI Centers of Excellence 2022 grant
Disentangling Transfer in Continual Reinforcement Learning Maciej Wołczyk , Michał Zając , Razvan Pascanu , Łukasz Kuciński , Piotr Miłoś NeurIPS 2022 paper
FlowHMM: Flow-based continuous hidden Markov models Paweł Lorek , Rafał Nowak , Tomasz Trzciński , Maciej Zięba NeurIPS 2022 paper
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models Kamil Deja , Anna Kuzina , Tomasz Trzciński , Jakub M. Tomczak NeurIPS 2022 paper
Interpretable Image Classification with Differentiable Prototypes Assignment Dawid Rymarczyk , Łukasz Struski , Michał Górszczak , Koryna Lewandowska , Jacek Tabor , Bartosz Zieliński ECCV 2022 paper
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification Dawid Rymarczyk , Adam Pardyl , Jarosław Kraus , Aneta Kaczyńska , Marek Skomorowski , Bartosz Zieliński ECML PKDD 2022 paper
LIDL: Local Intrinsic Dimension estimation using approximate Likelihood Piotr Tempczyk , Rafał Michaluk , Łukasz Garncarek , Przemysław Spurek , Jacek Tabor , Adam Golinski ICML (long presentation) 2022 paper
Continual Learning with Guarantees via Weight Interval Constraints Maciej Wołczyk , Karol Piczak , Bartosz Wójcik , Łukasz Pustelnik , Paweł Morawiecki , Jacek Tabor , Tomasz Trzciński , Przemysław Spurek ICML 2022 paper
Hypernetworks methods in Meta-Learning Przemysław Spurek Opus 22 2022 grant
BabyNet: Residual Transformer Module for Birth Weight Prediction on Fetal Ultrasound Video Szymon Płotka , Michał K. Grzeszczyk , Robert Brawura-Biskupski-Samaha , Paweł Gutaj , Michał Lipa , Tomasz Trzciński , Arkadiusz Sitek MICCAI 2022 paper
CoNeRF: Controllable Neural Radiance Fields. Computer Vision and Pattern Recognition Kacper Kania , Kwang Moo Yi , Marek Kowalski , Tomasz Trzciński , Andrea Tagliasacchi CVPR 2022 paper
Multiband VAE: Latent Space Partitioning for Knowledge Consolidation in Continual Learning Kamil Deja , Paweł Wawrzyński , Daniel Marczak , Wojciech Masarczyk , Tomasz Trzciński IJCAI 2022 paper
PluGeN: Multi-Label Conditional Generation From Pre-Trained Models Maciej Wołczyk , Magdalena Proszewska , Łukasz Maziarka , Maciej Zięba , Patryk Wielopolski , Rafał Kurczab , Marek Śmieja AAAI 2022 paper
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks Maciej Wołczyk , Bartosz Wójcik , Klaudia Bałazy , Igor Podolak , Jacek Tabor , Marek Śmieja , Tomasz Trzciński NeurIPS 2021 paper
Continual World: A Robotic Benchmark For Continual Reinforcement Learning Maciej Wołczyk , Michał Zając , Razvan Pascanu , Łukasz Kuciński , Piotr Miłoś NeurIPS 2021 paper
Non-Gaussian Gaussian Processes for Few-Shot Regression Marcin Sendera , Jacek Tabor , Aleksandra Nowak , Andrzej Bedychaj , Massimiliano Patacchiola , Tomasz Trzciński , Przemysław Spurek , Maciej Zięba NeurIPS 2021 paper
DUE: End-to-End Document Understanding Benchmark Łukasz Borchmann , Michał Pietruszka , Tomasz Stanisławek , Dawid Jurkiewicz , Michał Turski , Karolina Szyndler , Filip Graliński NeurIPS 2021 paper
MEiN scholarship for outstanding young scientists 2021 Tomasz Trzciński 2021 scholarship
MEiN scholarship for outstanding young scientists 2021 Marek Śmieja 2021 scholarship
START 2021 Stanisław Jastrzębski 2021 scholarship
ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification Dawid Rymarczyk , Łukasz Struski , Jacek Tabor , Bartosz Zieliński SIGKDD 2021 paper
Robust Learning-Augmented Caching: An Experimental Study Jakub Chłędowski , Adam Polak , Bartosz Szabucki , Konrad Żołna ICML 2021 paper
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization Stanisław Jastrzębski , Devansh Arpit , Oliver Astrand , Giancarlo Kerg , Huan Wang , Caiming Xiong , Richard Socher , Kyunghyun Cho* , Krzysztof Geras* ICML 2021 paper
Explaining Self-Supervised Image Representations with Visual Probing Dominika Basaj , Witold Oleszkiewicz , Igor Sieradzki , Michał Górszczak , Barbara Rychalska , Tomasz Trzciński , Bartosz Zieliński IJCAI 2021 paper
Kernel Self-Attention for Weakly-supervised Image Classification using Deep Multiple Instance Learning Dawid Rymarczyk , Adriana Borowa , Jacek Tabor , Bartosz Zieliński WACV 2021 paper
Combination of Molecular Simulation and Deep Learning for De Novo Drug Design Tomasz Danel Preludium 19 2020 grant
Cramer-Wold AutoEncoder Szymon Knop , Jacek Tabor , Przemysław Spurek , Igor Podolak , Marcin Mazur , Stanisław Jastrzębski JMLR 2020 paper
Finding the Optimal Network Depth in Classification Tasks Bartosz Wójcik , Maciej Wołczyk , Klaudia Bałazy , Jacek Tabor ECML PKDD 2020 paper
Hypernetwork approach to generating point clouds Przemysław Spurek , Sebastian Winczowski , Jacek Tabor , Maciej Zamorski , Maciej Zięba , Tomasz Trzciński ICML 2020 paper
Transformer-based methods for novel active chemical compounds Łukasz Maziarka Preludium 2020 grant
Evolutionary-Neural Hybrid Agents for Architecture Search Krzysztof Maziarz , Mingxing Tan , Andrey Khorlin , Marin Georgiev , Andrea Gesmundo ICML Workshop on AutoML 2019; 1st place in Data Science Masters - best Master's thesis competition, Applied track 2019 paper
Bio-inspired artificial neural networks Jacek Tabor FNP TEAM-NET 2019-2023 grant
The Break-Even Point on the Optimization Trajectories of Deep Neural Networks Stanisław Jastrzębski , Maciej Szymczak , Stanislav Fort , Devansh Arpit , Jacek Tabor , Kyunghyun Cho* , Krzysztof Geras* ICLR (Spotlight) 2020 paper
Persistence bag of words for topological data analysis Bartosz Zieliński , Michał Lipiński , Mateusz Juda , Matthias Zeppelzauer , Paweł Dłotko IJCAI 2019 paper
Parameter-Efficient Transfer Learning for NLP Neil Houlsby , Andrei Giurgiu , Stanisław Jastrzębski , Bruna Morrone , Quentin de Laroussilhe , Andrea Gesmundo , Mona Attariyan , Sylvain Gelly ICML 2019 paper
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length Stanisław Jastrzębski , Zachary Kenton , Nicolas Ballas , Asja Fischer , Yoshua Bengio , Amos Storkey ICLR 2019 paper
Distribution-Interpolation Trade off in Generative Models Damian Leśniak , Igor Sieradzki , Igor Podolak ICLR 2019 paper
Processing of missing data by neural networks Marek Śmieja , Łukasz Struski , Jacek Tabor , Bartosz Zieliński , Przemysław Spurek NeurIPS 2018 paper
Efficient unsupervised learning with applications in deep learning prof. Jacek Tabor , dr Marek Śmieja , dr Przemysław Spurek , dr Łukasz Struski NCN OPUS 13 2018-2021 grant
Deep Learning in representation of long sequential data mgr Konrad Żołna NCN ETIUDA 6 2018-2019 prize
Additional information in data clustering and related areas dr Marek Śmieja , dr Przemysław Spurek , dr Łukasz Struski 2017-2020 NCN SONATA 11 2017-2020 grant
New representation learning methods in Deep Learning mgr Stanisław Jastrzębski NCN ETIUDA 5 2017-2019 prize
Theory of missing data prof. Jacek Tabor , dr Łukasz Struski , dr Marek Śmieja , dr Bartosz Zieliński NCN OPUS 10 2016-2019 grant
Clustering algorithm, which uses generalized Gaussian distribution and non-normal distributions dr Przemysław Spurek NCN SONATA 10 2016-2019 grant
Detectors and descriptors of the key points based on the topological information dr Bartosz Zieliński , dr Mateusz Juda NCN SONATA 10 2016-2019 grant
Algorithmical aspects of synchronization dr Adam Roman NCN OPUS 9 2016-2019 grant
Best paper award at CORES'15 mgr Wojciech Czarnecki , dr hab. Jacek Tabor 2015 prize
Application of neural networks in politology dr hab. Igor Podolak (grant coordinated by dr hab. Łukasz Wordliczek) NCN OPUS 8 2015-2018 grant
Knowledge enriched sparse word embedding lic. Stanisław Jastrzębski (under supervision of dr hab. Jacek Tabor) MNiSW Diamentowy Grant 4 2015-2018 grant
Minimal Memory Clustering Paradigm dr hab. Jacek Tabor , dr hab. Igor Podolak , prof. dr hab. Andrzej Bojarski , mgr Przemysław Spurek , mgr Marek Śmieja , mgr Wojciech Czarnecki , mgr Sabina Smusz NCN OPUS 7 2015-2017 grant
Development of machine learning methods with applications to chemical compound activity prediction mgr Marek Śmieja NCN PRELUDIUM 7 2015-2017 grant
Rector prize for scientific achievements prof. Jacek Tabor , dr Wojciech Czarnecki , dr Przemysław Spurek UJ 2015 prize
Scholarship of Polish Minister Of Science lic. Stanisław Jastrzębski MNiSW 2015 prize
A novel approach to de novo genome assembly problem based on UCT mgr Ewa Matczyńska NCN PRELUDIUM 6 2014-2017 grant
The memory center mgr Przemysław Spurek NCN PRELUDIUM 5 2014-2017 grant
Novel active learning querying strategy for the machine learning models mgr Wojciech M. Czarnecki NCN PRELUDIUM 5 2014-2017 grant
4th place in TRADESHIFT competition lic. Stanisław Jastrzębski , Rafał Józefowicz (Google) , mgr Wojciech Czarnecki 2014 prize
5th place in CONNECTOMICS competition mgr Wojciech Czarnecki , Rafał Józefowicz (Google) 2014 prize
Entropy of the mixture of sources dr hab Jacek Tabor , mgr Marek Śmieja 2013-2015, NCN OPUS 1 grant
Second prize at the SMP competition Stanisław Jastrzębski (under supervision of dr hab. Igor Podolak) 2013 prize
Best presentation at CISIM'13 mgr Przemysław Spurek 2013 prize

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