Deep physical neural networks enabled by a backpropagation algorithm for
arbitrary physical systems

Deep physical neural networks enabled by a backpropagation algorithm for arbitrary physical systems

27 April 2021

Logan G. Wright

Tatsuhiro Onodera

Martin M. Stein

Darren T. Schachter

Peter L. McMahon

Papers citing "Deep physical neural networks enabled by a backpropagation algorithm for arbitrary physical systems"

18 / 18 papers shown

Title
Blending Optimal Control and Biologically Plausible Learning for Noise-Robust Physical Neural Networks S. Sunada T. Niiyama Kazutaka Kanno Rin Nogami André Röhm Takato Awano Atsushi Uchida AI4CE 50 1 0 26 Feb 2025
Analog In-memory Training on General Non-ideal Resistive Elements: The Impact of Response Functions Zhaoxian Wu Quan Xian Tayfun Gokmen Omobayode Fagbohungbe Tianyi Chen 91 0 0 17 Feb 2025
Scalable Back-Propagation-Free Training of Optical Physics-Informed Neural Networks Yequan Zhao Xinling Yu Xian Xiao Z. Chen Z. Liu G. Kurczveil R. Beausoleil S. Liu Z. Zhang 45 0 0 17 Feb 2025
Training Hybrid Neural Networks with Multimode Optical Nonlinearities Using Digital Twins Ilker Oguz Louis J. E. Suter J. Hsieh Mustafa Yildirim Niyazi Ulaş Dinç Christophe Moser D. Psaltis 48 2 0 14 Jan 2025
Training a multilayer dynamical spintronic network with standard machine learning tools to perform time series classification Erwan Plouet Dédalo Sanz-Hernández A. Vecchiola Julie Grollier F. Mizrahi 34 0 0 05 Aug 2024
A Pontryagin Perspective on Reinforcement Learning Onno Eberhard Claire Vernade Michael Muehlebach 33 2 0 28 May 2024
Gradient-based Design of Computational Granular Crystals Atoosa Parsa C. O’Hern Rebecca Kramer‐Bottiglio Josh Bongard 20 1 0 07 Apr 2024
Mathematical Algorithm Design for Deep Learning under Societal and Judicial Constraints: The Algorithmic Transparency Requirement Holger Boche Adalbert Fono Gitta Kutyniok FaML 23 4 0 18 Jan 2024
Deep Photonic Reservoir Computer for Speech Recognition Enrico Picco Alessandro Lupo Serge Massar 6 4 0 11 Dec 2023
Extending Neural Network Verification to a Larger Family of Piece-wise Linear Activation Functions László Antal Hana Masara Erika Ábrahám 15 0 0 16 Nov 2023
Nonlinear Processing with Linear Optics Mustafa Yildirim Niyazi Ulaş Dinç Ilker Oguz D. Psaltis C. Moser 35 32 0 17 Jul 2023
Backpropagation-free Training of Deep Physical Neural Networks Ali Momeni Babak Rahmani M. Malléjac Philipp del Hougne Romain Fleury AI4CE PINN 17 53 0 20 Apr 2023
Universal Approximation Property of Hamiltonian Deep Neural Networks M. Zakwan M. d’Angelo Giancarlo Ferrari-Trecate 13 5 0 21 Mar 2023
Hybrid training of optical neural networks J. Spall Xianxin Guo A. Lvovsky 25 38 0 20 Mar 2022
Learning on Arbitrary Graph Topologies via Predictive Coding Tommaso Salvatori Luca Pinchetti Beren Millidge Yuhang Song Tianyi Bao Rafal Bogacz Thomas Lukasiewicz 25 33 0 31 Jan 2022
Training a neural network with exciton-polariton optical nonlinearity A. Opala R. Panico V. Ardizzone B. Piętka J. Szczytko D. Sanvitto M. Matuszewski D. Ballarini 19 6 0 23 Jul 2021
Carbon Emissions and Large Neural Network Training David A. Patterson Joseph E. Gonzalez Quoc V. Le Chen Liang Lluís-Miquel Munguía D. Rothchild David R. So Maud Texier J. Dean AI4CE 239 626 0 21 Apr 2021
$All-Optical Machine Learning Using Diffractive Deep Neural Networks$ All-Optical Machine Learning Using Diffractive Deep Neural Networks Xing Lin Y. Rivenson N. Yardimci Muhammed Veli Mona Jarrahi Aydogan Ozcan 59 1,596 0 14 Apr 2018