Achievements
PhD defense | Analyzing Deep Neural Networks from a Graph Perspective | Aleksandra Nowak | 2025 | |
PhD defense | Deep learning under distribution shifts: continual learning and beyond | Michał Zając | 2025 | |
PRELUDIUM 24 | Boosting Neural Network Efficiency by Examining Early Training Patterns | Mateusz Pyla | 2025 | |
PRELUDIUM 24 | Democratizing Diffusion Models: Guidance-Driven Optimization of Existing Models for Enhanced Quality and Diversity with Compliance-Preserving Unlearning | Artur Kasymov | 2025 | |
PRELUDIUM 24 | Explanation of Pre-Trained deep learning models via Prototypes | Piotr Borycki | 2025 | |
PRELUDIUM 24 | Editing of a 3D object represented by Gaussian Splatting | Joanna Waczyńska | 2025 | |
OPUS 29 | Multimodal learning for medical image analysis | Szymon Płotka | 2025 | |
Medical Image Analysis | Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge | Szymon Płotka | 2025 | |
Knowledge-Based Systems | Hypernetwork Approach to Rapid NeRF Adaptation | Paweł Batorski, Dawid Malarz, Marcin Przewięźlikowski, Marcin Mazur, Sławomir Tadeja, Przemyslaw Spurek | 2025 | |
AAAI | Enhancing Chemical Explainability Through Counterfactual Masking | Łukasz Janisiów, Marek Kochańczyk, Bartosz Zieliński, Tomasz Danel | 2025 | |
AAAI | EPIC: Explanation of Pretrained Image Classification Networks via Prototypes | Piotr Borycki, Magda Trędowicz, Szymon Janusz, Jacek Tabor, Przemyslaw Spurek, Arkadiusz Lewicki, Łukasz Struski | 2025 | |
Habilitation | New properties of optimization of artificial neural networks | Stanisław Jastrzębski | 2025 | |
PhD defense | Adapting Deep Learning Architectures for Drug Discovery | Łukasz Maziarka | 2025 | |
European Patent Office | A method and a system for identifying polyculture bacteria on microscopic images using deep learning | Bartosz Zieliński, Adriana Borowa, Dawid Rymarczyk, Monika Brzychczy-Włoch, Dorota Ochońska, Agnieszka Sroka-Oleksiak, Barbara Brzychczy | 2025 | |
Witold Lipski Award | Witold Lipski Award for Young Computer Scientists (for the achievements in applied computer science) | Marcin Sendera | 2025 | |
MICCAI | GEPAR3D: Geometry Prior-Assisted Learning for 3D Tooth Segmentation | Tomasz Szczepański, Szymon Płotka, Michal K Grzeszczyk, Arleta Adamowicz, Piotr Fudalej, Przemysław Korzeniowski, Tomasz Trzciński, Arkadiusz Sitek | 2025 | |
NeurIPS | Mamba Goes HoME: Hierarchical Soft Mixture-of-Experts for 3D Medical Image Segmentation | Szymon Płotka, Gizem Mert, Maciej Chrabąszcz, Ewa Szczurek, Arkadiusz Sitek | 2025 | |
NeurIPS | URB - Urban Routing Benchmark for RL-equipped Connected Autonomous Vehicles | Ahmet Onur Akman, Anastasia Psarou, Michał Hoffmann, Łukasz Gorczyca, Lukasz Kowalski, Paweł Gora, Grzegorz Jamróz, Rafal Kucharski | 2025 | |
NeurIPS | FlySearch: Exploring how vision-language models explore | Adam Pardyl, Dominik Matuszek, Mateusz Przebieracz, Marek Cygan, Bartosz Zieliński, Maciej Wołczyk | 2025 | |
NeurIPS | ZEUS: Zero-shot Embeddings for Unsupervised Separation of Tabular Data | Patryk Marszałek, Tomasz Kuśmierczyk, Witold Wydmański, Jacek Tabor, Marek Śmieja | 2025 | |
NeurIPS | DiCoFlex: Model-Agnostic Diverse Counterfactuals with Flexible Control | Oleksii Furman, Ulvi Movsum-zada, Patryk Marszałek, Maciej Zięba, Marek Śmieja | 2025 | |
NeurIPS | Scalable and Cost-Efficient de Novo Template-Based Molecular Generation | Piotr Gaiński, Oussama Boussif, Andrei Rekesh, Dmytro Shevchuk, Ali Parviz, Mike Tyers, Robert A. Batey, Michał Koziarski | 2025 | |
NeurIPS | CLIPGaussian: Universal and Multimodal Style Transfer Based on Gaussian Splatting | Kornel Howil, Joanna Waczyńska, Piotr Borycki, Tadeusz Dziarmaga, Marcin Mazur, Przemyslaw Spurek | 2025 | |
PLOS Computational Biology | Deep learning approach for automatic assessment of schizophrenia and bipolar disorder in patients using R-R intervals | Kamil Książek, Wilhelm Masarczyk, Przemysław Głomb, Michał Romaszewski, Krisztián Buza, Przemysław Sekuła, Michał Cholewa, Katarzyna Kołodziej, Piotr Gorczyca, Magdalena Piegza | 2025 | |
EMNLP | Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRA | Patryk Marszałek, Klaudia Bałazy, Jacek Tabor, Tomasz Kuśmierczyk | 2025 |