Our paper on Spherical Boltzmann machines is accepted at #NeurIPS2026.
A solvable energy-based model where training-time phase transitions explain sampling temperature tuning, double descent, tempered posteriors, and more.
CNRS researcher working at the Institut de Physique Théorique (IPhT) in Paris-Saclay. Interested in statistical physics, machine learning, and biological data modeling. Website: sites.google.com/view/jorgefdcd