activity
20182021
most citedPhotonics for artificial intelligence and neuromorphic computing

1.7k citations · 1.7k across the 4 of their papers we have counts for

collaborators

11 papers

cs.LG20214 cited

Dynamic Precision Analog Computing for Neural Networks

Sahaj Garg, Joe Lou, Anirudh Jain +1

Analog electronic and optical computing exhibit tremendous advantages over digital computing for accelerating deep learning when operations are executed at low precision. In this w…

physics.app-ph20204 cited

A Laser Spiking Neuron in a Photonic Integrated Circuit

Mitchell A. Nahmias, Hsuan-Tung Peng, Thomas Ferreira de Lima +4

There has been a recent surge of interest in the implementation of linear operations such as matrix multipications using photonic integrated circuit technology. However, these appr…

physics.optics20201.7k cited

Photonics for artificial intelligence and neuromorphic computing

Bhavin J. Shastri, Alexander N. Tait, Thomas Ferreira de Lima +4

Research in photonic computing has flourished due to the proliferation of optoelectronic components on photonic integration platforms. Photonic integrated circuits have enabled ult…

physics.app-ph2019

Programmable Silicon Photonic Optical Thresholder

Chaoran Huang, Thomas Ferreira de Lima, Aashu Jha +4

We experimentally demonstrate an all-optical programmable thresholder on a silicon photonic circuit. By exploiting the nonlinearities in a resonator-enhanced Mach-Zehnder interfero…

physics.app-ph2019

Noise Analysis of Photonic Modulator Neurons

Thomas Ferreira de Lima, Alexander N. Tait, Hooman Saeidi +5

Neuromorphic photonics relies on efficiently emulating analog neural networks at high speeds. Prior work showed that transducing signals from the optical to the electrical domain a…

cs.NE2019

Takens-inspired neuromorphic processor: a downsizing tool for random recurrent neural networks via feature extraction

Bicky A. Marquez, Jose Suarez-Vargas, Bhavin J. Shastri

We describe a new technique which minimizes the amount of neurons in the hidden layer of a random recurrent neural network (rRNN) for time series prediction. Merging Takens-based a…