Hybrid Swarm and Agent-Based Evolutionary Optimization. - Leszek Placzkiewicz; Marcin Sendera; Adam Szlachta; Mateusz Paciorek; Aleksander Byrski; Marek Kisiel-Dorohinicki; Mateusz Godzik (ICCS (2), 2018)

Data adaptation in HANDY economy-ideology model. - Marcin Sendera (CoRR, 2019)

Supermodeling: The Next Level of Abstraction in the Use of Data Assimilation. - Marcin Sendera; Gregory S. Duane; Witold Dzwinel (ICCS (6), 2020)

Flow-based anomaly detection. - Lukasz Maziarka; Marek Smieja; Marcin Sendera; Lukasz Struski; Jacek Tabor; Przemyslaw Spurek (CoRR, 2020)

Missing Glow Phenomenon: Learning Disentangled Representation of Missing Data. - Marcin Sendera; Lukasz Struski; Przemyslaw Spurek (ICONIP (5), 2021)

Non-Gaussian Gaussian Processes for Few-Shot Regression. - Marcin Sendera; Jacek Tabor; Aleksandra Nowak 001; Andrzej Bedychaj; Massimiliano Patacchiola; Tomasz Trzcinski; Przemyslaw Spurek; Maciej Zieba (NeurIPS, 2021)

Flow-based SVDD for anomaly detection. - Marcin Sendera; Marek Smieja; Lukasz Maziarka; Lukasz Struski; Przemyslaw Spurek; Jacek Tabor (CoRR, 2021)

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)

HyperShot: Few-Shot Learning by Kernel HyperNetworks. - Marcin Sendera; Marcin Przewiezlikowski; Konrad Karanowski; Maciej Zieba; Jacek Tabor; Przemyslaw Spurek (WACV, 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., 2023)

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 001 (ICML, 2024)

Improved off-policy training of diffusion samplers. - Marcin Sendera; Minsu Kim 004; Sarthak Mittal; Pablo Lemos; Luca Scimeca; Jarrid Rector-Brooks; Alexandre Adam; Yoshua Bengio; Nikolay Malkin (NeurIPS, 2024)

Amortizing intractable inference in diffusion models for vision, language, and control. - Siddarth Venkatraman; Moksh Jain; Luca Scimeca; Minsu Kim 004; Marcin Sendera; Mohsin Hasan; Luke Rowe; Sarthak Mittal; Pablo Lemos; Emmanuel Bengio; Alexandre Adam; Jarrid Rector-Brooks; et al. (NeurIPS, 2024)

On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling. - Marcin Sendera; Minsu Kim 004; Sarthak Mittal; Pablo Lemos; Luca Scimeca; Jarrid Rector-Brooks; Alexandre Adam; Yoshua Bengio; Nikolay Malkin (CoRR, 2024)

AutoLoRA: AutoGuidance Meets Low-Rank Adaptation for Diffusion Models. - Artur Kasymov; Marcin Sendera; Michal Stypulkowski; Maciej Zieba; Przemyslaw Spurek (CoRR, 2024)

High-Fidelity Transfer of Functional Priors for Wide Bayesian Neural Networks by Learning Activations. - Marcin Sendera; Amin Sorkhei; Tomasz Kusmierczyk (CoRR, 2024)

Revisiting the Equivalence of Bayesian Neural Networks and Gaussian Processes: On the Importance of Learning Activations. - Marcin Sendera; Amin Sorkhei; Tomasz Kusmierczyk (UAI, 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, 2025)

Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models. - Siddarth Venkatraman; Mohsin Hasan; Minsu Kim 004; Luca Scimeca; Marcin Sendera; Yoshua Bengio; Glen Berseth; Nikolay Malkin (CoRR, 2025)

SEMU: Singular Value Decomposition for Efficient Machine Unlearning. - Marcin Sendera; Lukasz Struski; Kamil Ksiazek; Kryspin Musiol; Jacek Tabor; Dawid Rymarczyk (CoRR, 2025)

Solving Bayesian inverse problems with diffusion priors and off-policy RL. - Luca Scimeca; Siddarth Venkatraman; Moksh Jain; Minsu Kim 004; Marcin Sendera; Mohsin Hasan; Luke Rowe; Sarthak Mittal; Pablo Lemos; Emmanuel Bengio; Alexandre Adam; Jarrid Rector-Brooks; et al. (CoRR, 2025)

Hi-fi functional priors by learning activations. - Marcin Sendera; Amin Sorkhei; Tomasz Kusmierczyk (CoRR, 2025)