Sendera, Marcin

12 publications

TMLR 2026 From Discrete-Time Policies to Continuous-Time Diffusion Samplers: Asymptotic Equivalences and Faster Training Julius Berner, Lorenz Richter, Marcin Sendera, Jarrid Rector-Brooks, Nikolay Malkin
ICML 2025 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
ICLRW 2025 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
UAI 2025 Revisiting the Equivalence of Bayesian Neural Networks and Gaussian Processes: On the Importance of Learning Activations Marcin Sendera, Amin Sorkhei, Tomasz Kuśmierczyk
ICML 2025 SEMU: Singular Value Decomposition for Efficient Machine Unlearning Marcin Sendera, Łukasz Struski, Kamil Książek, Kryspin Musiol, Jacek Tabor, Dawid Damian Rymarczyk
ICLRW 2025 Solving Bayesian Inverse Problems with Diffusion Priors and Off-Policy RL Luca Scimeca, Siddarth Venkatraman, Moksh Jain, Minsu Kim, Marcin Sendera, Mohsin Hasan, Alexandre Adam, Yashar Hezaveh, Laurence Perreault-Levasseur, Yoshua Bengio, Glen Berseth, Nikolay Malkin
NeurIPS 2024 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
NeurIPSW 2024 Hi-Fi Functional Priors by Learning Activations Marcin Sendera, Amin Sorkhei, Tomasz Kuśmierczyk
NeurIPS 2024 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
ICML 2024 Iterated Denoising Energy Matching for Sampling from Boltzmann Densities Tara Akhound-Sadegh, Jarrid Rector-Brooks, Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong
WACV 2023 HyperShot: Few-Shot Learning by Kernel HyperNetworks Marcin Sendera, Marcin Przewięźlikowski, Konrad Karanowski, Maciej Zięba, Jacek Tabor, Przemysław Spurek
NeurIPS 2021 Non-Gaussian Gaussian Processes for Few-Shot Regression Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Tomasz Trzcinski, Przemysław Spurek, Maciej Zieba