Berggren, Karl https://orcid.org/0000-0001-7453-9031
Xia, Qiangfei https://orcid.org/0000-0003-1436-8423
Likharev, Konstantin K
Strukov, Dmitri B
Jiang, Hao
Mikolajick, Thomas https://orcid.org/0000-0003-3814-0378
Querlioz, Damien
Salinga, Martin https://orcid.org/0000-0002-2228-6244
Erickson, John R
Pi, Shuang
Xiong, Feng
Lin, Peng
Li, Can https://orcid.org/0000-0003-3795-2008
Chen, Yu
Xiong, Shisheng
Hoskins, Brian D
Daniels, Matthew W https://orcid.org/0000-0002-3390-4714
Madhavan, Advait
Liddle, James A
McClelland, Jabez J
Yang, Yuchao https://orcid.org/0000-0003-4674-4059
Rupp, Jennifer
Nonnenmann, Stephen S
Cheng, Kwang-Ting https://orcid.org/0000-0002-3885-4912
Gong, Nanbo https://orcid.org/0000-0002-9797-5124
Lastras-Montaño, Miguel Angel
Talin, A Alec
Salleo, Alberto
Shastri, Bhavin J https://orcid.org/0000-0001-5040-8248
de Lima, Thomas Ferreira
Prucnal, Paul
Tait, Alexander N
Shen, Yichen
Meng, Huaiyu
Roques-Carmes, Charles
Cheng, Zengguang https://orcid.org/0000-0002-2204-3429
Bhaskaran, Harish
Jariwala, Deep https://orcid.org/0000-0002-3570-8768
Wang, Han
Shainline, Jeffrey M https://orcid.org/0000-0002-6102-5880
Segall, Kenneth
Yang, J Joshua https://orcid.org/0000-0001-8242-7531
Roy, Kaushik
Datta, Suman
Raychowdhury, Arijit
Journal title: Nanotechnology
Article type: rev
Article title: Roadmap on emerging hardware and technology for machine learning
Copyright information: © 2020 IOP Publishing Ltd
License information: CC BY 4.0 Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Publication dates
Date received: 2019-11-20
Date accepted: 2020-07-17
Online publication date: 2020-10-19