Ernoult, Maxence

11 publications

NeurIPS 2025 Learning Long Range Dependencies Through Time Reversal Symmetry Breaking Guillaume Pourcel, Maxence Ernoult

NeurIPSW 2024 A Cookbook for Hardware-Friendly Implicit Learning on Static Data Maxence Ernoult, Rasmus Høier, Jack Kendall

NeurIPSW 2024 Casting Hybrid Digital-Analog Training into Hierarchical Energy-Based Learning Timothy Nest, Maxence Ernoult

NeurIPSW 2024 Dyadic Learning in Recurrent and Feedforward Models Rasmus Høier, Kirill Kalinin, Maxence Ernoult, Christopher Zach

NeurIPSW 2024 Dyadic Learning in Recurrent and Feedforward Models Rasmus Høier, Kirill Kalinin, Maxence Ernoult, Christopher Zach

NeurIPS 2024 Towards Training Digitally-Tied Analog Blocks via Hybrid Gradient Computation Timothy Nest, Maxence Ernoult

NeurIPS 2023 Energy-Based Learning Algorithms for Analog Computing: A Comparative Study Benjamin Scellier, Maxence Ernoult, Jack Kendall, Suhas Kumar

NeurIPSW 2023 Energy-Based Learning Algorithms for Analog Computing: A Comparative Study Benjamin Scellier, Maxence Ernoult, Jack Kendall, Suhas Kumar

ICMLW 2023 Energy-Based Learning Algorithms: A Comparative Study Benjamin Scellier, Maxence Ernoult, Jack Kendall, Suhas Kumar

CVPRW 2021 Training Dynamical Binary Neural Networks with Equilibrium Propagation Jérémie Laydevant, Maxence Ernoult, Damien Querlioz, Julie Grollier

NeurIPS 2019 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