scispace - formally typeset
Open AccessJournal ArticleDOI

Deep learning with coherent nanophotonic circuits

Reads0
Chats0
TLDR
A new architecture for a fully optical neural network is demonstrated that enables a computational speed enhancement of at least two orders of magnitude and three order of magnitude in power efficiency over state-of-the-art electronics.
Abstract
Artificial Neural Networks have dramatically improved performance for many machine learning tasks. We demonstrate a new architecture for a fully optical neural network that enables a computational speed enhancement of at least two orders of magnitude and three orders of magnitude in power efficiency over state-of-the-art electronics.

read more

Citations
More filters
Proceedings ArticleDOI

A Silicon Photonic Accelerator for Convolutional Neural Networks with Heterogeneous Quantization

TL;DR: HQNNA is proposed, a CNN accelerator based on non-coherent silicon photonics that can accelerate both homogeneously quantized and heterogeneous quantized CNN models, and achieves up to 73.8x better energy-per-bit and 159.5x better throughput-energy efficiency than state-of-the-art photonic CNN accelerators.
Journal ArticleDOI

Mathematical operations and equation solving with reconfigurable metadevices

TL;DR: In this paper , the authors report the theory and design of wave-based metastructures using tunable elements capable of solving integral/differential equations in a fully-reconfigurable fashion.
Journal ArticleDOI

Addressing limited weight resolution in a fully optical neuromorphic reservoir computing readout.

TL;DR: In this paper, the authors investigate a method for improving the performance of optical weighting components, even in the presence of noise and in the case of very low resolution, using an iterative training procedure and select weight connections that are more robust to quantization and noise.
Journal ArticleDOI

On-Chip Nonreciprocal Photonic Devices Based on Hybrid Integration of Magneto-Optical Garnet Thin Films on Silicon

TL;DR: In this article , the authors review the progress of on-chip non-reciprocal photonic devices based on hybrid integration of magneto-optical (MO) thin films on silicon.
Journal ArticleDOI

Ultrafast machine vision with artificial neural network devices based on a GaN-based micro-LED array

TL;DR: In this paper, the authors measured the characteristics of micro-LED based photodetector experimentally and proposed a feasible simulation of a novel artificial neural network (ANN) device for the first time.
References
More filters
Proceedings Article

ImageNet Classification with Deep Convolutional Neural Networks

TL;DR: The state-of-the-art performance of CNNs was achieved by Deep Convolutional Neural Networks (DCNNs) as discussed by the authors, which consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully-connected layers with a final 1000-way softmax.
Journal ArticleDOI

Deep learning

TL;DR: Deep learning is making major advances in solving problems that have resisted the best attempts of the artificial intelligence community for many years, and will have many more successes in the near future because it requires very little engineering by hand and can easily take advantage of increases in the amount of available computation and data.
Journal ArticleDOI

Human-level control through deep reinforcement learning

TL;DR: This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.
Journal ArticleDOI

Reducing the Dimensionality of Data with Neural Networks

TL;DR: In this article, an effective way of initializing the weights that allows deep autoencoder networks to learn low-dimensional codes that work much better than principal components analysis as a tool to reduce the dimensionality of data is described.
Journal ArticleDOI

Deep learning in neural networks

TL;DR: This historical survey compactly summarizes relevant work, much of it from the previous millennium, review deep supervised learning, unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
Related Papers (5)