Achievements
UAI | Revisiting the Equivalence of Bayesian Neural Networks and Gaussian Processes: On the Importance of Learning Activations | Marcin Sendera, Amin Sorkhei, Tomasz Kuśmierczyk | 2025 | |
ICML | Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers | Filip Szatkowski, Yaoyue Zheng, Fei Yang, Tomasz Trzcinski, Bartłomiej Twardowski, Joost van de Weijer | 2025 | |
ICML | MiraGe: Editable 2D Images using Gaussian Splatting | Joanna Waczyńska, Tomasz Szczepanik, Piotr Borycki, Sławomir Tadeja, Thomas Bohné, Przemyslaw Spurek | 2025 | |
ICML | How to Train Your Multi-Exit Model? Analyzing the Impact of Training Strategies | Piotr Kubaty, Bartosz Wójcik, Bartłomiej Krzepkowski, Monika Michaluk, Tomasz Trzcinski, Jary Pomponi, Aamil Adamczewski | 2025 | |
ICML | Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models | Siddarth Venkatraman, Mohsin Hasan, Minsu Kim, Luca Scimeca, Marcin Sendera, Yoshua Bengio, Glen Berseth, Nikolay Malkin | 2025 | |
ICML | SEMU: Singular Value Decomposition for Efficient Machine Unlearning | Marcin Sendera, Łukasz Struski, Kamil Książek, Kryspin Musiol, Jacek Tabor, Dawid Rymarczyk | 2025 | |
Information Sciences | HINT: Hypernetwork Approach to Training Weight Interval Regions in Continual Learning | Patryk Krukowski, Anna Bielawska, Kamil Książek, Paweł Wawrzyński, Paweł Batorski, Przemyslaw Spurek | 2025 | |
LIDER XV | A virtual assistant for medical screening tests powered by artificial intelligence | Tomasz Danel | 2025 | |
Information Sciences | NegGS: Negative Gaussian Splatting | Artur Kasymov, Bartosz Czekaj, Marcin Mazur, Jacek Tabor, Przemyslaw Spurek | 2025 | |
ICLR | FreSh: Frequency Shifting for Accelerated Neural Representation Learning | Adam Kania, Marko Mihajlovic, Sergey Prokudin, Jacek Tabor, Przemyslaw Spurek | 2025 | |
ICLR | LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision | Mateusz Pach, Koryna Lewandowska, Jacek Tabor, Bartosz Michał Zieliński, Dawid Damian Rymarczyk | 2025 | |
SDM | VisTabNet: Adapting Vision Transformers for Tabular Data | Witold Wydmański, Ulvi Movsum-zada, Jacek Tabor, Marek Śmieja | 2025 | |
SDM | Parameter-Efficient Interventions for Enhanced Model Merging | Marcin Osial, Daniel Marczak, Bartosz Zieliński | 2025 | |
CVPR | Workshop on Computer Vision for Drug Discovery: Where Are We and What is Beyond? | Dawid Rymarczyk, Ada Borowa, Ilknur Icke, Chao-Hui Huang, Ana Sanchez-Fernandez, Anne Carpenter | 2025 | |
AAAI | Adaptive Computation Modules: Granular Conditional Computation For Efficient Inference | Bartosz Wójcik, Alessio Devoto, Karol Pustelnik, Pasquale Minervini, Simone Scardapane | 2025 | |
ICLR | Workshop on Sparsity in LLMs (SLLM): Deep Dive into Mixture of Experts, Quantization, Hardware, and Inference | Tianlong Chen, Utku Evci, Yani Ioannou, Berivan Isik, Shiwei Liu, Mohammed Adnan, Aleksandra Nowak, Ashwinee Panda | 2025 | |
Prime Minister's Prize in the category of outstanding doctoral dissertation. | Outstanding doctoral dissertation: Deep Learning Methods in Pharmaceutical Sciences | Tomasz Danel | 2024 | |
WACV | Beyond Grids: Exploring Elastic Input Sampling for Vision Transformers | Adam Pardyl, Grzegorz Kurzejamski, Jan Olszewski, Tomasz Trzciński, Bartosz Zieliński | 2025 | |
Knowledge-Based Systems | Augmentation-aware Self-supervised Learning with Conditioned Projector | Marcin Przewięźlikowski, Mateusz Pyla, Bartosz Zieliński, Bartłomiej Twardowski, Jacek Tabor, Marek Śmieja | 2024 | |
NeurIPS | D-MiSo: Editing Dynamic 3D Scenes using Multi-Gaussians Soup | Joanna Waczyńska, Piotr Borycki, Joanna Kaleta, Sławomir Tadeja, Przemysław Spurek | 2024 | |
NeurIPS | Exploiting Activation Sparsity with Dense to Dynamic-k Mixture-of-Experts Conversion | Filip Szatkowski, Bartosz Wójcik, Mikołaj Piórczyński, Simone Scardapane | 2024 | |
NeurIPS | RGFN: Synthesizable Molecular Generation Using GFlowNets | Michał Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer van der Sloot, Piotr Gaiński, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, Robert A. Batey | 2024 | |
NeurIPS | Amortizing intractable inference in diffusion models for vision, language, and control | Siddarth Venkatraman*, Moksh Jain*, Luca Scimeca*, Minsu Kim*, Marcin Sendera*, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin | 2024 | |
NeurIPS | Improved off-policy training of diffusion samplers | Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin | 2024 | |
WACV | Token Recycling for Efficient Sequential Inference with Vision Transformers | Jan Olszewski, Dawid Rymarczyk, Piotr Wójcik, Mateusz Pach, Bartosz Zieliński | 2025 |