2 citations · 2 across the 3 of their papers we have counts for
4 papers
Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations
Witold Oleszkiewicz, Dominika Basaj, Igor Sieradzki +5
Recently introduced self-supervised methods for image representation learning provide on par or superior results to their fully supervised competitors, yet the corresponding effort…
Differences between human and machine perception in medical diagnosis
Taro Makino, Stanislaw Jastrzebski, Witold Oleszkiewicz +18
Deep neural networks (DNNs) show promise in image-based medical diagnosis, but cannot be fully trusted since their performance can be severely degraded by dataset shifts to which h…
Understanding the robustness of deep neural network classifiers for breast cancer screening
Witold Oleszkiewicz, Taro Makino, Stanisław Jastrzębski +5
Deep neural networks (DNNs) show promise in breast cancer screening, but their robustness to input perturbations must be better understood before they can be clinically implemented…
Siamese Generative Adversarial Privatizer for Biometric Data
Witold Oleszkiewicz, Peter Kairouz, Karol Piczak +2
State-of-the-art machine learning algorithms can be fooled by carefully crafted adversarial examples. As such, adversarial examples present a concrete problem in AI safety. In this…