42 citations · 100 across the 18 of their papers we have counts for
5 papers · 1 filter
Physics-aware Differentiable Discrete Codesign for Diffractive Optical Neural Networks
Yingjie Li, Ruiyang Chen, Weilu Gao +1
Diffractive optical neural networks (DONNs) have attracted lots of attention as they bring significant advantages in terms of power efficiency, parallelism, and computational speed…
Perfectly Perform Machine Learning Task with Imperfect Optical Hardware Accelerator
Jichao Fan, Yingheng Tang, Weilu Gao
Optical architectures have been emerging as an energy-efficient and high-throughput hardware platform to accelerate computationally intensive general matrix-matrix multiplications…
Device-system Co-design of Photonic Neuromorphic Processor using Reinforcement Learning
Yingheng Tang, Princess Tara Zamani, Ruiyang Chen +4
The incorporation of high-performance optoelectronic devices into photonic neuromorphic processors can substantially accelerate computationally intensive operations in machine lear…
Physics-aware Complex-valued Adversarial Machine Learning in Reconfigurable Diffractive All-optical Neural Network
Ruiyang Chen, Yingjie Li, Minhan Lou +5
Diffractive optical neural networks have shown promising advantages over electronic circuits for accelerating modern machine learning (ML) algorithms. However, it is challenging to…
Evidence for Phonon-Assisted Intertube Electronic Transport in an Armchair Carbon Nanotube Film
Davoud Adinehloo, Weilu Gao, Ali Mojibpour +2
The electrical conductivity of a macroscopic assembly of nanomaterials is determined through a complex interplay of electronic transport within and between constituent nano-objects…