Marcin Sendera

According to our database, Marcin Sendera authored at least 22 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Hi-fi functional priors by learning activations.

Marcin Sendera, Amin Sorkhei, Tomasz Kusmierczyk

CoRR, August, 2025

Solving Bayesian inverse problems with diffusion priors and off-policy RL.

Luca Scimeca, Siddarth Venkatraman, Moksh Jain, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yashar Hezaveh, Laurence Perreault Levasseur, Yoshua Bengio, Glen Berseth, Nikolay Malkin

CoRR, March, 2025

SEMU: Singular Value Decomposition for Efficient Machine Unlearning.

Marcin Sendera, Lukasz Struski, Kamil Ksiazek, Kryspin Musiol, Jacek Tabor, Dawid Rymarczyk

CoRR, February, 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

CoRR, February, 2025

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

CoRR, January, 2025

Revisiting the Equivalence of Bayesian Neural Networks and Gaussian Processes: On the Importance of Learning Activations.

Marcin Sendera, Amin Sorkhei, Tomasz Kusmierczyk

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

2024

High-Fidelity Transfer of Functional Priors for Wide Bayesian Neural Networks by Learning Activations.

Marcin Sendera, Amin Sorkhei, Tomasz Kusmierczyk

CoRR, 2024

AutoLoRA: AutoGuidance Meets Low-Rank Adaptation for Diffusion Models.

Artur Kasymov, Marcin Sendera, Michal Stypulkowski, Maciej Zieba, Przemyslaw Spurek

CoRR, 2024

On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling.

Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 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

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Iterated Denoising Energy Matching for Sampling from Boltzmann Densities.

Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

The general framework for few-shot learning by kernel HyperNetworks.

Marcin Sendera, Marcin Przewiezlikowski, Jan Miksa, Mateusz Rajski, Konrad Karanowski, Maciej Zieba, Jacek Tabor, Przemyslaw Spurek

Mach. Vis. Appl., July, 2023

HyperShot: Few-Shot Learning by Kernel HyperNetworks.

Marcin Sendera, Marcin Przewiezlikowski, Konrad Karanowski, Maciej Zieba, Jacek Tabor, Przemyslaw Spurek

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

2022

OneFlow: One-Class Flow for Anomaly Detection Based on a Minimal Volume Region.

Lukasz Maziarka, Marek Smieja, Marcin Sendera, Lukasz Struski, Jacek Tabor, Przemyslaw Spurek

IEEE Trans. Pattern Anal. Mach. Intell., 2022

2021

Flow-based SVDD for anomaly detection.

Marcin Sendera, Marek Smieja, Lukasz Maziarka, Lukasz Struski, Przemyslaw Spurek, Jacek Tabor

CoRR, 2021

Non-Gaussian Gaussian Processes for Few-Shot Regression.

Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Tomasz Trzcinski, Przemyslaw Spurek, Maciej Zieba

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Missing Glow Phenomenon: Learning Disentangled Representation of Missing Data.

Marcin Sendera, Lukasz Struski, Przemyslaw Spurek

Proceedings of the Neural Information Processing - 28th International Conference, 2021

2020

Flow-based anomaly detection.

Lukasz Maziarka, Marek Smieja, Marcin Sendera, Lukasz Struski, Jacek Tabor, Przemyslaw Spurek

CoRR, 2020

Supermodeling: The Next Level of Abstraction in the Use of Data Assimilation.

Marcin Sendera, Gregory S. Duane, Witold Dzwinel

Proceedings of the Computational Science - ICCS 2020, 2020

2019

Data adaptation in HANDY economy-ideology model.

Marcin Sendera

CoRR, 2019

2018

Hybrid Swarm and Agent-Based Evolutionary Optimization.

Leszek Placzkiewicz, Marcin Sendera, Adam Szlachta, Mateusz Paciorek, Aleksander Byrski, Marek Kisiel-Dorohinicki, Mateusz Godzik

Proceedings of the Computational Science - ICCS 2018, 2018