3 citations · 3 across the 5 of their papers we have counts for
5 papers
Optical Implementation of Equilibrium Propagation Using Spatial Photonic Ising Machines
Dimitri Vanden Abeele, Daniele Veraldi, Davide Pierangeli +2
Equilibrium Propagation offers a compelling alternative to traditional machine learning for training energy-based networks. Here we demonstrate a hybrid optical-digital implementat…
Information Processing Capacity of Stationary Physical Systems: Theory, Data-efficient Estimation Methods, and Photonic Demonstration
Rahul Uma Ramachandran, Serge Massar
Physical computing systems provide a promising route toward hardware-native machine learning, but their computational capabilities remain difficult to characterize in a principled,…
Equilibrium Propagation for Non-Conservative Systems
Antonino Emanuele Scurria, Dimitri Vanden Abeele, Bortolo Matteo Mognetti +1
Equilibrium Propagation (EP) is a physics-inspired learning algorithm that uses stationary states of a dynamical system both for inference and learning. In its original formulation…
Equilibrium Propagation for Learning in Lagrangian Dynamical Systems
Serge Massar
We propose a method for training dynamical systems governed by Lagrangian mechanics using Equilibrium Propagation. Our approach extends Equilibrium Propagation - initially develope…
Equilibrium Propagation: the Quantum and the Thermal Cases
Serge Massar, Bortolo Matteo Mognetti
Equilibrium propagation is a recently introduced method to use and train artificial neural networks in which the network is at the minimum (more generally extremum) of an energy fu…