2 papers
cs.LG2025
Smooth InfoMax -- Towards Easier Post-Hoc Interpretability
Fabian Denoodt, Bart de Boer, José Oramas
We introduce Smooth InfoMax (SIM), a self-supervised representation learning method that incorporates interpretability constraints into the latent representations at different dept…
cs.LG2025
Efficient Post-Hoc Uncertainty Calibration via Variance-Based Smoothing
Fabian Denoodt, José Oramas
Since state-of-the-art uncertainty estimation methods are often computationally demanding, we investigate whether incorporating prior information can improve uncertainty estimates…