From the 1 of 3 linked papers with an AI index.
3 papers
Equilibrium Training of Energy-Based Models with Parallel Trajectory Tempering
Nicolas Béreux, Aurélien Decelle, Cyril Furtlehner +1
The paper proposes Parallel Trajectory Tempering (PTT), a training method that keeps equilibrium sampling throughout learning of energy‑based models, enabling fast and stable train…
Uncovering statistical structure in large-scale neural activity with Restricted Boltzmann Machines
Nicolas Béreux, Giovanni Catania, Aurélien Decelle +3
Large-scale electrophysiological recordings now allow simultaneous monitoring of thousands of neurons across multiple brain regions, revealing structured variability in neural popu…
Fast training and sampling of Restricted Boltzmann Machines
Nicolas Béreux, Aurélien Decelle, Cyril Furtlehner +2
Restricted Boltzmann Machines (RBMs) are powerful tools for modeling complex systems and extracting insights from data, but their training is hindered by the slow mixing of Markov…