Opto-electronic memristors: Prospects and challenges in neuromorphic computing-Reference-Cited by-同舟云学术

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Opto-electronic memristors: Prospects and challenges in neuromorphic computing

Published:2020-12-07 Issue:23 Volume:117 Page:230502
ISSN:0003-6951
Container-title:Applied Physics Letters
language:en
Short-container-title:Appl. Phys. Lett.

Author:

Emboras Alexandros¹^ORCID,Alabastri Alessandro²^ORCID,Lehmann Paul¹,Portner Kevin¹^ORCID,Weilenmann Christoph¹,Ma Ping³^ORCID,Cheng Bojun³,Lewerenz Mila³,Passerini Elias³,Koch Ueli³,Aeschlimann Jan¹^ORCID,Ducry Fabian¹,Leuthold Juerg³^ORCID,Luisier Mathieu¹^ORCID

Affiliation:

1. Integrated Systems Laboratory (IIS), ETH Zurich, 8092 Zurich, Switzerland

2. Department of Electrical and Computer Engineering, Rice University, Houston, Texas 77005, USA

3. Institute of Electromagnetic Fields (IEF), ETH Zurich, 8092 Zurich, Switzerland

Funder

Werner Siemens Stiftung

Swiss National Supercomputing Center

ETH Zurich

Publisher

AIP Publishing

Subject

Physics and Astronomy (miscellaneous)

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0028539

Reference69 articles.

1. Dermatologist-level classification of skin cancer with deep neural networks

2. A systematic approach to identify novel cancer drug targets using machine learning, inhibitor design and high-throughput screening

3. Deep learning with long short-term memory networks for financial market predictions

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