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Marcin Sendera
Marcin Sendera
PhD Student, Jagiellonian University, Research Intern at Mila - Quebec AI Institute,
Zweryfikowany adres z doctoral.uj.edu.pl
Tytuł
Cytowane przez
Cytowane przez
Rok
Hypershot: Few-shot learning by kernel hypernetworks
M Sendera, M Przewięźlikowski, K Karanowski, M Zięba, J Tabor, ...
Proceedings of the IEEE/CVF winter conference on applications of computer …, 2023
342023
Iterated denoising energy matching for sampling from Boltzmann densities
T Akhound-Sadegh, J Rector-Brooks, AJ Bose, S Mittal, P Lemos, CH Liu, ...
arXiv preprint arXiv:2402.06121, 2024
272024
Improved off-policy training of diffusion samplers
M Sendera, M Kim, S Mittal, P Lemos, L Scimeca, J Rector-Brooks, ...
Advances in Neural Information Processing Systems 37, 81016-81045, 2025
24*2025
Non-gaussian gaussian processes for few-shot regression
M Sendera, J Tabor, A Nowak, A Bedychaj, M Patacchiola, T Trzcinski, ...
Advances in Neural Information Processing Systems 34, 10285-10298, 2021
202021
Amortizing intractable inference in diffusion models for vision, language, and control
S Venkatraman, M Jain, L Scimeca, M Kim, M Sendera, M Hasan, L Rowe, ...
arXiv preprint arXiv:2405.20971, 2024
182024
Supermodeling: the next level of abstraction in the use of data assimilation
M Sendera, GS Duane, W Dzwinel
Computational Science–ICCS 2020: 20th International Conference, Amsterdam …, 2020
92020
Hybrid swarm and agent-based evolutionary optimization
L Placzkiewicz, M Sendera, A Szlachta, M Paciorek, A Byrski, ...
Computational Science–ICCS 2018: 18th International Conference, Wuxi, China …, 2018
82018
Oneflow: One-class flow for anomaly detection based on a minimal volume region
Ł Maziarka, M Śmieja, M Sendera, Ł Struski, J Tabor, P Spurek
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 8508 …, 2021
6*2021
Data adaptation in handy economy-ideology model
M Sendera
arXiv preprint arXiv:1904.04309, 2019
62019
The general framework for few-shot learning by kernel HyperNetworks
M Sendera, M Przewiȩźlikowski, J Miksa, M Rajski, K Karanowski, ...
Machine Vision and Applications 34 (4), 53, 2023
42023
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training
J Berner, L Richter, M Sendera, J Rector-Brooks, N Malkin
arXiv preprint arXiv:2501.06148, 2025
22025
AutoLoRA: AutoGuidance Meets Low-Rank Adaptation for Diffusion Models
A Kasymov, M Sendera, M Stypułkowski, M Zięba, P Spurek
arXiv preprint arXiv:2410.03941, 2024
12024
Early detection and diagnosis of cancer with interpretable machine learning to uncover cancer-specific DNA methylation patterns
I Newsham, M Sendera, SG Jammula, SA Samarajiwa
Biology Methods and Protocols 9 (1), 2024
12024
SEMU: Singular Value Decomposition for Efficient Machine Unlearning
M Sendera, Ł Struski, K Książek, K Musiol, J Tabor, D Rymarczyk
arXiv preprint arXiv:2502.07587, 2025
2025
Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models
S Venkatraman, M Hasan, M Kim, L Scimeca, M Sendera, Y Bengio, ...
arXiv preprint arXiv:2502.06999, 2025
2025
High-Fidelity Transfer of Functional Priors for Wide Bayesian Neural Networks by Learning Activations
M Sendera, A Sorkhei, T Kuśmierczyk
arXiv preprint arXiv:2410.15777, 2024
2024
Missing Glow Phenomenon: Learning Disentangled Representation of Missing Data
M Sendera, Ł Struski, P Spurek
International Conference on Neural Information Processing, 196-204, 2021
2021
Flow-based SVDD for anomaly detection
M Sendera, M Śmieja, Ł Maziarka, Ł Struski, P Spurek, J Tabor
arXiv preprint arXiv:2108.04907, 2021
2021
Amortizing intractable inference in diffusion models for Bayesian inverse problems
S Venkatraman, M Jain, L Scimeca, M Kim, M Sendera, M Hasan, L Rowe, ...
Hi-fi functional priors by learning activations
M Sendera, A Sorkhei, T Kuśmierczyk
NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty, 0
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