Vowel recognition with four coupled spin-torque nano-oscillators. - Miguel Romera; Philippe Talatchian; Sumito Tsunegi; Flavio Abreu Araujo; Vincent Cros; Paolo Bortolotti; Juan Trastoy; Kay Yakushiji; Akio Fukushima; Hitoshi Kubota; Shinji Yuasa; Maxence Ernoult; et al. (Nat., 2018)

Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input. - Maxence Ernoult; Julie Grollier; Damien Querlioz; Yoshua Bengio; Benjamin Scellier (NeurIPS, 2019)

Microwave neural processing and broadcasting with spintronic nano-oscillators. - Philippe Talatchian; M. Romera; Sumito Tsunegi; Flavio Abreu Araujo; Vincent Cros; Paolo Bortolotti; Juan Trastoy; Kay Yakushiji; Akio Fukushima; Hitoshi Kubota; Shinji Yuasa; Maxence Ernoult; et al. (CoRR, 2019)

Synaptic Metaplasticity in Binarized Neural Networks. - Axel Laborieux; Maxence Ernoult; Tifenn Hirtzlin; Damien Querlioz (CoRR, 2020)

Equilibrium Propagation with Continual Weight Updates. - Maxence Ernoult; Julie Grollier; Damien Querlioz; Yoshua Bengio; Benjamin Scellier (CoRR, 2020)

Continual Weight Updates and Convolutional Architectures for Equilibrium Propagation. - Maxence Ernoult; Julie Grollier; Damien Querlioz; Yoshua Bengio; Benjamin Scellier (CoRR, 2020)

Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias. - Axel Laborieux; Maxence Ernoult; Benjamin Scellier; Yoshua Bengio; Julie Grollier; Damien Querlioz (CoRR, 2020)

EqSpike: Spike-driven Equilibrium Propagation for Neuromorphic Implementations. - Erwann Martin; Maxence Ernoult; Jérémie Laydevant; Shuai Li; Damien Querlioz; Teodora Petrisor; Julie Grollier (CoRR, 2020)

Rethinking biologically inspired learning algorithmstowards better credit assignment for on-chip learning. (Repenser les algorithmes d'apprentissage inspirés de la biologie pour estimer les gradients par la physique des systèmes neuromorphiques). - Maxence Ernoult (2020)

Training Dynamical Binary Neural Networks With Equilibrium Propagation. - Jérémie Laydevant; Maxence Ernoult; Damien Querlioz; Julie Grollier (CVPR Workshops, 2021)

Towards Scaling Difference Target Propagation by Learning Backprop Targets. - Maxence Ernoult; Fabrice Normandin; Abhinav Moudgil; Sean Spinney; Eugene Belilovsky; Irina Rish; Blake A. Richards; Yoshua Bengio (ICML, 2022)

Energy-based learning algorithms for analog computing: a comparative study. - Benjamin Scellier; Maxence Ernoult; Jack D. Kendall; Suhas Kumar (NeurIPS, 2023)

Towards training digitally-tied analog blocks via hybrid gradient computation. - Timothy Nest; Maxence Ernoult (NeurIPS, 2024)

Learning long range dependencies through time reversal symmetry breaking. - Guillaume Pourcel; Maxence Ernoult (CoRR, 2025)

Lagrangian-based Equilibrium Propagation: generalisation to arbitrary boundary conditions & equivalence with Hamiltonian Echo Learning. - Guillaume Pourcel; Debabrota Basu; Maxence Ernoult; Aditya Gilra (CoRR, 2025)