Invertible Neural Networks for Design of Broadband Active Mixers-Reference-Cited by-同舟云学术

Invertible Neural Networks for Design of Broadband Active Mixers

Published:2022-09-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 ACM/IEEE Workshop on Machine Learning for CAD
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Author:

Akinwande Oluwaseyi¹,Waqar Bhatti Osama¹,Li Xingchen¹,Swaminathan Madhavan¹

Affiliation:

1. Georgia Institute of Technology, Atlanta, GA, USA

Funder

Center for Advanced Electronics through Machine Learning (CAEML)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3551901.3556491

Reference20 articles.

1. Nikita Ambasana Osama W. Bhatti Majid A. Dolatsara Madhavan Swaminathan Xianbo Yang Pavel R. Paladhi and Wiren Dale Becker. 2021. Invertible Neural Networks for High-Speed Channel Design & Parameter Distribution Estimation. In 2021 IEEE 30th Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS). 1--3. https://doi.org/10.1109/EPEPS51341.2021.9609225 Nikita Ambasana Osama W. Bhatti Majid A. Dolatsara Madhavan Swaminathan Xianbo Yang Pavel R. Paladhi and Wiren Dale Becker. 2021. Invertible Neural Networks for High-Speed Channel Design & Parameter Distribution Estimation. In 2021 IEEE 30th Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS). 1--3. https://doi.org/10.1109/EPEPS51341.2021.9609225

2. Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert Daniel Rahner Eric Pellegrini Ralf S. Klessen Lena Maier-Hein Carsten Rother and U. Köthe. 2019. Analyzing Inverse Problems with Invertible Neural Networks. ArXiv Vol. abs/1808.04730 (2019). Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert Daniel Rahner Eric Pellegrini Ralf S. Klessen Lena Maier-Hein Carsten Rother and U. Köthe. 2019. Analyzing Inverse Problems with Invertible Neural Networks. ArXiv Vol. abs/1808.04730 (2019).

3. Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert Daniel Rahner Eric Pellegrini Ralf S. Klessen Lena Maier-Hein Carsten Rother and U. Köthe. 2021. Framework for Easily Invertible Architectures (FrEIA). https://github.com/VLL-HD/FrEIA Retrieved June 2022 from Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert Daniel Rahner Eric Pellegrini Ralf S. Klessen Lena Maier-Hein Carsten Rother and U. Köthe. 2021. Framework for Easily Invertible Architectures (FrEIA). https://github.com/VLL-HD/FrEIA Retrieved June 2022 from

4. Inverse Design of Power Delivery Networks using Invertible Neural Networks

5. Laurent Dinh , Jascha Narain Sohl-Dickstein, and Samy Bengio . 2017 . Density estimation using Real NVP. ArXiv , Vol. abs/ 1605 .08803 (2017). Laurent Dinh, Jascha Narain Sohl-Dickstein, and Samy Bengio. 2017. Density estimation using Real NVP. ArXiv, Vol. abs/1605.08803 (2017).