3 papers
cs.LG2026
RAMP: Recognition parametrisation by Amortised Message Passing
Lior Fox, Kai Biegun, James Heald +3
A central aim of unsupervised learning is to uncover latent factors that explain dependencies among observations. Probabilistic models typically achieve this by introducing multipl…
cs.LG2025
Maximum Likelihood Learning of Latent Dynamics Without Reconstruction
Samo Hromadka, Kai Biegun, Lior Fox +2
We introduce a novel unsupervised learning method for time series data with latent dynamical structure: the recognition-parametrized Gaussian state space model (RP-GSSM). The RP-GS…
cs.AI2025
Is there Value in Reinforcement Learning?
Lior Fox, Yonatan Loewenstein
Action-values play a central role in popular Reinforcement Learing (RL) models of behavior. Yet, the idea that action-values are explicitly represented has been extensively debated…