2 papers
cs.LG2022
Homomorphism Autoencoder -- Learning Group Structured Representations from Observed Transitions
Hamza Keurti, Hsiao-Ru Pan, Michel Besserve +2
How can agents learn internal models that veridically represent interactions with the real world is a largely open question. As machine learning is moving towards representations c…
cs.LG2021
Uncertainty estimation under model misspecification in neural network regression
Maria R. Cervera, Rafael Dätwyler, Francesco D'Angelo +3
Although neural networks are powerful function approximators, the underlying modelling assumptions ultimately define the likelihood and thus the hypothesis class they are parameter…