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Achievements | GMUM

Achievements

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
WACV
GeoGuide: Geometric guidance of diffusion models
Mateusz Poleski, Jacek Tabor, Przemysław Spurek
2025
Neurocomputing
HyperMAML: Few-Shot Adaptation of Deep Models with Hypernetworks
Marcin Przewięźlikowski, Przemysław Przybysz, Jacek Tabor, Maciej Zięba, Przemysław Spurek
2024
ECCV
AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale
Adam Pardyl, Michał Wronka, Maciej Wołczyk, Kamil Adamczewski, Tomasz Trzciński, Bartosz Zieliński
2024
FIRST TEAM FENG
Interpretowalne i interaktywne wielomodalne wyszukiwanie w procesie odkrywania leków.
Bartosz Zieliński
2024
FIRST TEAM FENG
Efektywne renderowanie obiektów 3D reprezentowanych za pomocą NeRF w środowisku rozszerzonej rzeczywistości.
Przemyslaw Spurek
2024
ECML PKDD
A deep cut into Split Federated Self-Supervised Learning
Marcin Przewięźlikowski, Marcin Osial, Marek Śmieja, Bartosz Zieliński
2024
ICML
Sparser, Better, Deeper, Stronger: Improving Sparse Training with Exact Orthogonal Initialization
Aleksandra Nowak, Łukasz Gniecki, Filip Szatkowski, Jacek Tabor
2024
ICLR
Prediction Error-based Classification for Class-Incremental Learning
Michał Zając, Tinne Tuytelaars, Gido M. van de Ven
2024
ICLR
Divide and not forget Ensemble of selectively trained experts in Continual Learning
Grzegorz Rypeść, Sebastian Cygert, Valeriya Khan, Tomasz Trzcinski, Bartosz Zieliński, Bartłomiej Twardowski
2024
AAMAS
Modelling the Rise and Fall of Two-Sided Mobility Markets with Microsimulation
Farnoud Ghasemi, Rafał Kucharski
2024
AAAI
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations
Mikołaj Sacha, Bartosz Jura, Dawid Rymarczyk, Łukasz Struski, Jacek Tabor, Bartosz Zieliński
2024
OPUS 25
Meta-learning in Deep Neural Networks
Jacek Tabor
2023
PRELUDIUM 22
Where to look next - guiding active visual exploration with internal model uncertainty
Adam Pardyl
2023
PRELUDIUM 22
Improving the transferability of self-supervised learning models
Marcin Przewięźlikowski
2023
PRELUDIUM 22
Computationally efficient dynamic neural networks
Bartosz Wójcik
2023
PhD defense
Deep generative models in image processing
Szymon Knop
2023
PhD defense
Deep learning methods in pharmaceutical sciences
Tomasz Danel
2023
Contact us:
Group of Machine Learning Research
Faculty of Mathematics and Computer Science
ul. Lojasiewicza 6
30-342, Cracow, Poland
© 2024 — GMUM
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