Najnowsze publikacje
- Przemysław Spurek, Marcin Sendera, Marcin Przewięźlikowski, Jan Miksa, Mateusz Rajski, Konrad Karanowski, Maciej Zieba, Jacek Tabor, The general framework for few-shot learning by kernel HyperNetworks, Machine Vision and Applications 34 (2023), 53
- Przemysław Spurek, Jacek Tabor, Marcin Sendera, Marcin Przewięźlikowski, Konrad Karanowski, Zięba Maciej, Hypershot: Few-shot learning by kernel hypernetworks, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2023), 2469--2478
- Łukasz Maziarka, Marek Śmieja, Marcin Sendera, Łukasz Struski, Jacek Tabor, Przemysław Spurek, OneFlow: One-class flow for anomaly detection based on a minimal volume region, IEEE Transactions on Pattern Analysis and Machine Intelligence 44/11 (2022), 8508-8519
- Marcin Sendera, Przemysław Spurek, Łukasz Struski, Missing Glow Phenomenon: learning disentangled representation of missing data, International Conference on Neural Information Processing [ICONIP] vol 1516 (2021), 196-204
- Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Przemysław Spurek, Tomasz Trzciński, Zięba Maciej, Non-Gaussian Gaussian Processes for Few-Shot Regression, Advances in Neural Information Processing Systems [NeurIPS](MAIN) 34 (2021), 10285-10298
Marcin Sendera
stopień/tytuł magister statusdoktorant informatyki
grupa badawcza
- Group of Machine Learning Research (GMUM)
marcin.sendera@doctoral.uj.edu.pl