Research
Total Ionizing Dose Assessment of a Commercial 200V PMOSFET
July 18, 2018
Abstract
Total ionizing dose testing of commercial 200 V PMOSFETs. At 100 kRad(Si), observed VT increase of ~ 3 V for biased ON devices and increase of ~ 1 V for biased OFF devices. The RDS_ON did not degrade with dose.
Related Publications
February 27, 2025
Integrity
Theory
Logic.py: Bridging the Gap between LLMs and Constraint Solvers
Pascal Kesseli, Peter O'Hearn, Ricardo Silveira Cabral
February 27, 2025
February 06, 2025
Speech & Audio
Meta Audiobox Aesthetics: Unified Automatic Quality Assessment for Speech, Music, and Sound
Andros Tjandra, Yi-Chiao Wu, Baishan Guo, John Hoffman, Brian Ellis, Apoorv Vyas, Bowen Shi, Sanyuan Chen, Matt Le, Nick Zacharov, Carleigh Wood, Ann Lee, Wei-Ning Hsu
February 06, 2025
February 06, 2025
NLP
Brain-to-Text Decoding: A Non-invasive Approach via Typing
Jarod Levy, Mingfang (Lucy) Zhang, Svetlana Pinet, Jérémy Rapin, Hubert Jacob Banville, Stéphane d'Ascoli, Jean Remi King
February 06, 2025
February 06, 2025
NLP
From Thought to Action: How a Hierarchy of Neural Dynamics Supports Language Production
Mingfang (Lucy) Zhang, Jarod Levy, Stéphane d'Ascoli, Jérémy Rapin, F.-Xavier Alario, Pierre Bourdillon, Svetlana Pinet, Jean Remi King
February 06, 2025
April 08, 2021
Responsible AI
Integrity
Towards measuring fairness in AI: the Casual Conversations dataset
Caner Hazirbas, Joanna Bitton, Brian Dolhansky, Jacqueline Pan, Albert Gordo, Cristian Canton Ferrer
April 08, 2021
April 30, 2018
The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings | Facebook AI Research
Tomer Galanti, Lior Wolf, Sagie Benaim
April 30, 2018
April 30, 2018
Computer Vision
NAM – Unsupervised Cross-Domain Image Mapping without Cycles or GANs | Facebook AI Research
Yedid Hoshen, Lior Wolf
April 30, 2018
December 11, 2019
Speech & Audio
Computer Vision
Hyper-Graph-Network Decoders for Block Codes | Facebook AI Research
Eliya Nachmani, Lior Wolf
December 11, 2019
Help Us Pioneer The Future of AI
We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.
Foundational models
Our approach
Latest news
Foundational models
Meta © 2025