Cover Image

Scalable Back-Propagation-Free Training of Optical Physics-Informed Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhao, Yequan, Yu, Xinling, Xiao, Xian, Chen, Zhixiong, Liu, Ziyue, Kurczveil, Geza, Beausoleil, Raymond G., Liu, Sijia, Zhang, Zheng
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Real-Time FJ/MAC PDE Solvers via Tensorized, Back-Propagation-Free Optical PINN Training
by: Zhao, Yequan, et al.
Published: (2023)

Experimental Demonstration of an Optical Neural PDE Solver via On-Chip PINN Training
by: Zhao, Yequan, et al.
Published: (2025)

A Non-Volatile Heterogeneous Quantum Dot III-V/Si DFB Laser with Optical Memristive Behavior
by: Cheung, Stanley, et al.
Published: (2026)

Poor Man's Training on MCUs: A Memory-Efficient Quantized Back-Propagation-Free Approach
by: Zhao, Yequan, et al.
Published: (2024)

Separable Operator Networks
by: Yu, Xinling, et al.
Published: (2024)

Ultra‐Power‐Efficient, Electrically Programmable, Multi‐State Photonic Flash Memory on a Heterogeneous III‐V/Si Platform
by: Stanley Cheung, et al.
Published: (2024)

TEON: Tensorized Orthonormalization Beyond Layer-Wise Muon for Large Language Model Pre-Training
by: Zhang, Ruijie, et al.
Published: (2026)

Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes
by: Zhong, Ming, et al.
Published: (2024)

Physics-Informed Deep Recurrent Back-Projection Network for Tunnel Propagation Modeling
by: Wu, Kunyu, et al.
Published: (2026)

MuonQ: Enhancing Low-Bit Muon Quantization via Directional Fidelity Optimization
by: Su, Yupeng, et al.
Published: (2026)

Photonic KAN: a Kolmogorov-Arnold network inspired efficient photonic neuromorphic architecture
by: Peng, Yiwei, et al.
Published: (2024)

Research on Flight Accidents Prediction based Back Propagation Neural Network
by: Liu, Haoxing, et al.
Published: (2024)

Tensor-Compressed and Fully-Quantized Training of Neural PDE Solvers
by: Lu, Jinming, et al.
Published: (2025)

Dual Natural Gradient Descent for Scalable Training of Physics-Informed Neural Networks
by: Jnini, Anas, et al.
Published: (2025)

Discontinuity Computing using Physics-Informed Neural Network
by: Liu, Li, et al.
Published: (2022)

ssProp: Energy-Efficient Training for Convolutional Neural Networks with Scheduled Sparse Back Propagation
by: Zhong, Lujia, et al.
Published: (2024)

Scalable Quantum Error Mitigation with Physically Informed Graph Neural Networks
by: Wang, Huaxin, et al.
Published: (2026)

Commonsense Knowledge Editing Based on Free-Text in LLMs
by: Huang, Xiusheng, et al.
Published: (2024)

Training Large-Scale Optical Neural Networks with Two-Pass Forward Propagation
by: Ahmadnejad, Amirreza, et al.
Published: (2024)

A Consolidated Volatility Prediction with Back Propagation Neural Network and Genetic Algorithm
by: Ke, Zong, et al.
Published: (2024)

FBLNet: FeedBack Loop Network for Driver Attention Prediction
by: Chen, Yilong, et al.
Published: (2022)

ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks
by: Wu, Haixu, et al.
Published: (2025)

Muon$^2$: Boosting Muon via Adaptive Second-Moment Preconditioning
by: Liu, Ziyue, et al.
Published: (2026)

MUON+: Towards More Effective Muon via One Additional Normalization Step for LLM Pre-training
by: Zhang, Ruijie, et al.
Published: (2026)

ConFIG: Towards Conflict-free Training of Physics Informed Neural Networks
by: Liu, Qiang, et al.
Published: (2024)

Training Deep Normalization-Free Spiking Neural Networks with Lateral Inhibition
by: Liu, Peiyu, et al.
Published: (2025)

Modeling Terahertz Propagation via Frequency-Domain Physics-Informed Neural Networks
by: Zhu, Pengfei, et al.
Published: (2025)

Graph Coarsening via Supervised Granular-Ball for Scalable Graph Neural Network Training
by: Xia, Shuyin, et al.
Published: (2024)

SEPhIA: <1 laser/neuron Spiking Electro-Photonic Integrated Multi-Tiled Architecture for Scalable Optical Neuromorphic Computing
by: Hejda, Matěj, et al.
Published: (2025)

One-side oscillation strategic approach
by: Ricardo Beausoleil
Published: (2013)

Physics Informed Neural Networks for Free Shear Flows
by: Raghu, Siddharth, et al.
Published: (2024)

Training of Spiking Neural Networks with Expectation-Propagation
by: Yao, Dan, et al.
Published: (2025)

Flexible Strain Sensor Enabled by Back Propagation Neural Network for Gesture Recognition
by: Yikai Wu, et al.
Published: (2025)

Optical Inversion and Spectral Unmixing of Spectroscopic Photoacoustic Images with Physics-Informed Neural Networks
by: Ter Martirosyan, Sarkis, et al.
Published: (2026)

DeepOHeat-v1: Efficient Operator Learning for Fast and Trustworthy Thermal Simulation and Optimization in 3D-IC Design
by: Yu, Xinling, et al.
Published: (2025)

Scalability of On-chip Diffractive Optical Neural Networks
by: Zarei, Sanaz
Published: (2024)

Preconditioning for Physics-Informed Neural Networks
by: Liu, Songming, et al.
Published: (2024)

Improved Training of Physics-Informed Neural Networks with Model Ensembles
by: Haitsiukevich, Katsiaryna, et al.
Published: (2022)

Lightweight Geometric Adaptation for Training Physics-Informed Neural Networks
by: An, Kang, et al.
Published: (2026)

Defending against Backdoor Attack on Deep Neural Networks
by: Cheng, Hao, et al.
Published: (2020)