[HTML][HTML] Recent advances in physical reservoir computing: A review

G Tanaka, T Yamane, JB Héroux, R Nakane… - Neural Networks, 2019 - Elsevier
Reservoir computing is a computational framework suited for temporal/sequential data
processing. It is derived from several recurrent neural network models, including echo state …

Recent advances and future prospects for memristive materials, devices, and systems

MK Song, JH Kang, X Zhang, W Ji, A Ascoli… - ACS …, 2023 - ACS Publications
Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …

[PDF][PDF] Deep learning

I Goodfellow - 2016 - synapse.koreamed.org
An introduction to a broad range of topics in deep learning, covering mathematical and
conceptual background, deep learning techniques used in industry, and research …

Deep learning with coherent nanophotonic circuits

Y Shen, NC Harris, S Skirlo, M Prabhu… - Nature …, 2017 - nature.com
Artificial neural networks are computational network models inspired by signal processing in
the brain. These models have dramatically improved performance for many machine …

Finn: A framework for fast, scalable binarized neural network inference

Y Umuroglu, NJ Fraser, G Gambardella… - Proceedings of the …, 2017 - dl.acm.org
Research has shown that convolutional neural networks contain significant redundancy, and
high classification accuracy can be obtained even when weights and activations are …

[BOOK][B] Deep learning

Y Bengio, I Goodfellow, A Courville - 2017 - academia.edu
Inventors have long dreamed of creating machines that think. Ancient Greek myths tell of
intelligent objects, such as animated statues of human beings and tables that arrive full of …

FPGA-based accelerators of deep learning networks for learning and classification: A review

A Shawahna, SM Sait, A El-Maleh - ieee Access, 2018 - ieeexplore.ieee.org
Due to recent advances in digital technologies, and availability of credible data, an area of
artificial intelligence, deep learning, has emerged and has demonstrated its ability and …

Photonic machine learning with on-chip diffractive optics

T Fu, Y Zang, Y Huang, Z Du, H Huang, C Hu… - Nature …, 2023 - nature.com
Abstract Machine learning technologies have been extensively applied in high-performance
information-processing fields. However, the computation rate of existing hardware is …

FINN-R An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks

M Blott, TB Preußer, NJ Fraser, G Gambardella… - ACM Transactions on …, 2018 - dl.acm.org
Convolutional Neural Networks have rapidly become the most successful machine-learning
algorithm, enabling ubiquitous machine vision and intelligent decisions on even embedded …

Survey of machine learning accelerators

A Reuther, P Michaleas, M Jones… - 2020 IEEE high …, 2020 - ieeexplore.ieee.org
New machine learning accelerators are being announced and released each month for a
variety of applications from speech recognition, video object detection, assisted driving, and …