3 papers
cs.LG2026
Lagrangian-based Equilibrium Propagation: generalisation to arbitrary boundary conditions & equivalence with Hamiltonian Echo Learning
Guillaume Pourcel, Debabrota Basu, Maxence Ernoult +1
Equilibrium Propagation (EP) is a learning algorithm for training Energy-based Models (EBMs) on static inputs which leverages the variational description of their fixed points. Ext…
cs.LG2026
VertAX: a differentiable vertex model for learning epithelial tissue mechanics
Alessandro Pasqui, Jim Martin Catacora Ocana, Anshuman Sinha +7
Epithelial tissues dynamically reshape through local mechanical interactions among cells, a process well captured by vertex models. Yet their many tunable parameters make inference…
cs.LG2025
Learning long range dependencies through time reversal symmetry breaking
Guillaume Pourcel, Maxence Ernoult
Deep State Space Models (SSMs) reignite physics-grounded compute paradigms, as RNNs could natively be embodied into dynamical systems. This calls for dedicated learning algorithms…