3 papers
cs.CV2026
BARRIER: Bounded Activation Regions for Robust Information Erasure
Jan Miksa, Patryk Krukowski, Przemysław Spurek +2
Machine unlearning aims to remove targeted concepts from a trained model while preserving the rest of its knowledge. Central challenge of this setting is that effective and robust…
cs.LG2025
Hi-fi functional priors by learning activations
Marcin Sendera, Amin Sorkhei, Tomasz Kuśmierczyk
Function-space priors in Bayesian Neural Networks (BNNs) provide a more intuitive approach to embedding beliefs directly into the model's output, thereby enhancing regularization,…
cs.LG2024
Revisiting the Equivalence of Bayesian Neural Networks and Gaussian Processes: On the Importance of Learning Activations
Marcin Sendera, Amin Sorkhei, Tomasz Kuśmierczyk
Gaussian Processes (GPs) provide a convenient framework for specifying function-space priors, making them a natural choice for modeling uncertainty. In contrast, Bayesian Neural Ne…