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Found 5 papers, 0 papers with code
Real-Time FJ/MAC PDE Solvers via Tensorized, Back-Propagation-Free Optical PINN Training
Despite the ultra-high speed of optical neural networks, training a PINN on an optical chip is hard due to (1) the large size of photonic devices, and (2) the lack of scalable optical memory devices to store the intermediate results of back-propagation (BP).
High-Speed and Energy-Efficient Non-Volatile Silicon Photonic Memory Based on Heterogeneously Integrated Memresonator
Recently, interest in programmable photonics integrated circuits has grown as a potential hardware framework for deep neural networks, quantum computing, and field programmable arrays (FPGAs).
Tensorized Optical Multimodal Fusion Network
We propose the first tensorized optical multimodal fusion network architecture with a self-attention mechanism and low-rank tensor fusion.
Generative Neural Network Based Non-Convex Optimization Using Policy Gradients with an Application to Electromagnetic Design
A generative neural network based non-convex optimization algorithm using a one-step implementation of the policy gradient method is introduced and applied to electromagnetic design.
Inverse Design of Grating Couplers Using the Policy Gradient Method from Reinforcement Learning
We present a proof-of-concept technique for the inverse design of electromagnetic devices motivated by the policy gradient method in reinforcement learning, named PHORCED (PHotonic Optimization using REINFORCE Criteria for Enhanced Design).
