Wave Physics as an Analog Recurrent Neural Network

29 April 2019

Papers citing "Wave Physics as an Analog Recurrent Neural Network"

50 / 50 papers shown

Title
MAPS: Multi-Fidelity AI-Augmented Photonic Simulation and Inverse Design Infrastructure Pingchuan Ma Zhengqi Gao Meng Zhang Haoyu Yang Mark Ren Rena Huang Duane S. Boning Jiaqi Gu 41 0 0 02 Mar 2025
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 71 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
Discovery and inversion of the viscoelastic wave equation in inhomogeneous media Su Chen Yi Ding Hiroe Miyake Xiaojun Li 39 0 0 27 Sep 2024
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 49 0 0 05 Aug 2024
PIC2O-Sim: A Physics-Inspired Causality-Aware Dynamic Convolutional Neural Operator for Ultra-Fast Photonic Device FDTD Simulation Pingchuan Ma Haoyu Yang Zhengqi Gao Duane S. Boning Jiaqi Gu 34 3 0 24 Jun 2024
Towards Exact Gradient-based Training on Analog In-memory Computing Zhaoxian Wu Tayfun Gokmen Malte J. Rasch Tianyi Chen 26 2 0 18 Jun 2024
Training of Physical Neural Networks Ali Momeni Babak Rahmani B. Scellier Logan G. Wright Peter L. McMahon ... Julie Grollier Andrea J. Liu D. Psaltis Andrea Alù Romain Fleury PINN AI4CE 51 9 0 05 Jun 2024
Training all-mechanical neural networks for task learning through in situ backpropagation Shuaifeng Li Xiaoming Mao AI4CE 31 1 0 23 Apr 2024
Gradient-based Design of Computational Granular Crystals Atoosa Parsa C. O’Hern Rebecca Kramer‐Bottiglio Josh Bongard 28 1 0 07 Apr 2024
Unified, Verifiable Neural Simulators for Electromagnetic Wave Inverse Problems Charles Dove Jatearoon Boondicharern Laura Waller AI4CE 19 0 0 31 Mar 2024
Deep Learning in Deterministic Computational Mechanics L. Herrmann Stefan Kollmannsberger AI4CE PINN 43 0 0 27 Sep 2023
Analogue and Physical Reservoir Computing Using Water Waves I. Maksymov 24 16 0 15 Jun 2023
Backpropagation-free Training of Deep Physical Neural Networks Ali Momeni Babak Rahmani M. Malléjac Philipp del Hougne Romain Fleury AI4CE PINN 29 54 0 20 Apr 2023
Physics-inspired Neuroacoustic Computing Based on Tunable Nonlinear Multiple-scattering Ali Momeni Xinxin Guo Hervé Lissek Romain Fleury 16 5 0 17 Apr 2023
$Universal Linear Intensity Transformations Using Spatially-Incoherent Diffractive Processors$ Universal Linear Intensity Transformations Using Spatially-Incoherent Diffractive Processors Md. Sadman Sakib Rahman Xilin Yang Jingxi Li Bijie Bai Aydogan Ozcan 29 46 0 23 Mar 2023
An Analysis of Physics-Informed Neural Networks E. Small PINN 11 1 0 06 Mar 2023
Ultrafast single-channel machine vision based on neuro-inspired photonic computing Tomoya Yamaguchi Kohei Arai T. Niiyama Atsushi Uchida S. Sunada 24 9 0 15 Feb 2023
Dual adaptive training of photonic neural networks Ziyang Zheng Zhengyang Duan Hang Chen Rui Yang Sheng Gao Haiou Zhang H. Xiong Xing Lin 19 30 0 09 Dec 2022
Geometry-Complete Perceptron Networks for 3D Molecular Graphs Alex Morehead Jianlin Cheng GNN 3DV AI4CE 29 12 0 04 Nov 2022
Over-the-Air Split Machine Learning in Wireless MIMO Networks YuZhi Yang Zhaoyang Zhang Yuqing Tian Zhaohui Yang Chongwen Huang C. Zhong Kai‐Kit Wong 26 23 0 07 Oct 2022
Physical Computing for Materials Acceleration Platforms Erik J Peterson Alexander Lavin 11 3 0 17 Aug 2022
$Massively Parallel Universal Linear Transformations using a Wavelength-Multiplexed Diffractive Optical Network$ Massively Parallel Universal Linear Transformations using a Wavelength-Multiplexed Diffractive Optical Network Jingxi Li Bijie Bai Yilin Luo Aydogan Ozcan 29 48 0 13 Aug 2022
Machine learning for knowledge acquisition and accelerated inverse-design for non-Hermitian systems W. Ahmed M. Farhat K. Staliūnas Xiangliang Zhang Ying Wu 14 8 0 28 Apr 2022
$Polarization Multiplexed Diffractive Computing: All-Optical Implementation of a Group of Linear Transformations Through a Polarization-Encoded Diffractive Network$ Polarization Multiplexed Diffractive Computing: All-Optical Implementation of a Group of Linear Transformations Through a Polarization-Encoded Diffractive Network Jingxi Li Yi-Chun Hung Onur Kulce Deniz Mengu Aydogan Ozcan 30 66 0 25 Mar 2022
Learning Stochastic Dynamics with Statistics-Informed Neural Network Yuanran Zhu Yunhao Tang Changho Kim 19 18 0 24 Feb 2022
Neural network is heterogeneous: Phase matters more Yuqi Nie Hui Yuan 60 3 0 03 Nov 2021
Acceleration Method for Learning Fine-Layered Optical Neural Networks K. Aoyama H. Sawada 21 1 0 01 Sep 2021
Wave-based extreme deep learning based on non-linear time-Floquet entanglement Ali Momeni Romain Fleury 24 20 0 19 Jul 2021
Inverse Design of Grating Couplers Using the Policy Gradient Method from Reinforcement Learning S. Hooten R. Beausoleil T. Van Vaerenbergh 28 21 0 30 Jun 2021
Deep physical neural networks enabled by a backpropagation algorithm for arbitrary physical systems Logan G. Wright Tatsuhiro Onodera Martin M. Stein Tianyu Wang Darren T. Schachter Zoey Hu Peter L. McMahon PINN AI4CE 40 469 0 27 Apr 2021
Tensor Network for Supervised Learning at Finite Temperature Haoxiang Lin Shuqian Ye Xi Zhu 20 0 0 09 Apr 2021
Partial Differential Equations is All You Need for Generating Neural Architectures -- A Theory for Physical Artificial Intelligence Systems Ping Guo Kaizhu Huang Zenglin Xu AI4CE 14 3 0 10 Mar 2021
Self-learning Machines based on Hamiltonian Echo Backpropagation V. López-Pastor F. Marquardt 38 32 0 08 Mar 2021
Gaussian boson sampling and multi-particle event optimization by machine learning in the quantum phase space Claudio Conti 11 1 0 24 Feb 2021
Time-Continuous Energy-Conservation Neural Network for Structural Dynamics Analysis Yuan Feng Hexiang Wang Han Yang Fangbo Wang AI4CE 9 6 0 16 Dec 2020
$Scale-, shift- and rotation-invariant diffractive optical networks$ Scale-, shift- and rotation-invariant diffractive optical networks Deniz Mengu Y. Rivenson Aydogan Ozcan 52 65 0 24 Oct 2020
Nonseparable Symplectic Neural Networks S. Xiong Yunjin Tong Xingzhe He Shuqi Yang Cheng Yang Bo Zhu 29 32 0 23 Oct 2020
$Ensemble learning of diffractive optical networks$ Ensemble learning of diffractive optical networks Md. Sadman Sakib Rahman Jingxi Li Deniz Mengu Y. Rivenson Aydogan Ozcan 11 110 0 15 Sep 2020
$Large-scale neuromorphic optoelectronic computing with a reconfigurable diffractive processing unit$ Large-scale neuromorphic optoelectronic computing with a reconfigurable diffractive processing unit Tiankuang Zhou Xing Lin Jiamin Wu Yitong Chen Hao Xie Yipeng Li Jingtao Fan Huaqiang Wu Lu Fang Qionghai Dai BDL 28 419 0 26 Aug 2020
$All-Optical Information Processing Capacity of Diffractive Surfaces$ All-Optical Information Processing Capacity of Diffractive Surfaces Onur Kulce Deniz Mengu Y. Rivenson Aydogan Ozcan 13 111 0 25 Jul 2020
Deep neural networks for the evaluation and design of photonic devices Jiaqi Jiang Ming-Keh Chen Jonathan A. Fan 19 393 0 30 Jun 2020
$Terahertz Pulse Shaping Using Diffractive Surfaces$ Terahertz Pulse Shaping Using Diffractive Surfaces Muhammed Veli Deniz Mengu N. Yardimci Yilin Luo Jingxi Li Y. Rivenson Mona Jarrahi Aydogan Ozcan 25 4 0 30 Jun 2020
Neural Vortex Method: from Finite Lagrangian Particles to Infinite Dimensional Eulerian Dynamics S. Xiong Xingzhe He Yunjin Tong Yitong Deng Bo Zhu 21 11 0 07 Jun 2020
$Misalignment Resilient Diffractive Optical Networks$ Misalignment Resilient Diffractive Optical Networks Deniz Mengu Yifan Zhao N. Yardimci Y. Rivenson Mona Jarrahi Aydogan Ozcan 23 99 0 23 May 2020
Compatible Learning for Deep Photonic Neural Network Yong-Liang Xiao Rongguang Liang Jianxin Zhong X. Su Zhisheng You 16 1 0 14 Mar 2020
Photonic tensor cores for machine learning M. Miscuglio V. Sorger 14 147 0 01 Feb 2020
Theory of neuromorphic computing by waves: machine learning by rogue waves, dispersive shocks, and solitons G. Marcucci D. Pierangeli Claudio Conti 21 109 0 15 Dec 2019
$Class-specific Differential Detection in Diffractive Optical Neural Networks Improves Inference Accuracy$ Class-specific Differential Detection in Diffractive Optical Neural Networks Improves Inference Accuracy Jingxi Li Deniz Mengu Yilin Luo Y. Rivenson Aydogan Ozcan 11 111 0 08 Jun 2019
$All-Optical Machine Learning Using Diffractive Deep Neural Networks$ All-Optical Machine Learning Using Diffractive Deep Neural Networks Xing Lin Y. Rivenson N. Yardimci Muhammed Veli Mona Jarrahi Aydogan Ozcan 76 1,628 0 14 Apr 2018