Marcin Przewięźlikowski

Augmentation-aware self-supervised learning with conditioned projector, Knowledge-Based Systems (2024),

RegFlow: Probabilistic Flow-Based Regression for Future Prediction, Asian Conference on Intelligent Information and Database Systems [ACIIDS], (2024), 267–279

HyperMAML: Few-shot adaptation of deep models with hypernetworks, Neurocomputing (2024), 128-179

A deep cut into Split Federated Self-Supervised Learning, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database [ECML PKDD](MAIN), (2024), 444-459

Zero time waste in pre-trained early exit neural networks, Neural Networks vol. 168 (2023), 580-601

The general framework for few-shot learning by kernel HyperNetworks, Machine Vision and Applications vol. 34 (2023), 53

Hypershot: Few-shot learning by kernel hypernetworks, IEEE Workshop on Applications of Computer Vision [WACV](MAIN), (2023), 2469--2478

MisConv: Convolutional Neural Networks for Missing Data, IEEE Workshop on Applications of Computer Vision [WACV], (2022), 2060-2069

Estimating conditional density of missing values using deep Gaussian mixture model, International Conference on Neural Information Processing [ICONIP] vol. Lecture Notes in Computer Science volume 12534 (2020), 220-231

Estimating conditional density of missing values using deep Gaussian mixture model, International Conference On Machine Learning (workshop Track) (2020), 6