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@gpu-mode
GPU MODE gpu-mode
Your favorite GPU reading group https://discord.gg/gpumode
@mit-han-lab
MIT HAN Lab mit-han-lab
Efficient AI Computing. PI: Song Han

MIT

@jeonsworld
Eunkwang Jeon jeonsworld
live in simulation

Seoul, Republic of Korea

@liuzechun
Zechun Liu liuzechun
Research Scientist at Meta

Pittsburgh, USA

@lpcvai
Low Power Computer Vision lpcvai
Codebase for 2020 Low Power Computer Vision Challenge (LPCVC) and previous 2015 - 2019 Low Power Image Recognition Challenge (LPIRC).

Purdue University

@extreme-assistant
CVMart extreme-assistant
面向视觉算法开发者的极市社区,微信公众号:极市平台(extrememart)

Extreme Vision Limited Shenzhen,china

@Yangqing
Yangqing Jia Yangqing
Startup. Former VP @alibaba. Ex-@facebook @google @BVLC. Created Caffe, @caffe2, @onnx. Co-led @pytorch 1.0. @tensorflow contributor. @ucberkeley alumni.

@leptonai Berkeley

@longcw
Long Chen longcw

@livekit Changsha, China

@renmengye
Mengye Ren renmengye
Assistant Professor at NYU Courant & Center for Data Science

NYU New York, NY

@yunjey
Yunjey Choi yunjey

NAVER AI Lab South Korea

@ruotianluo
Ruotian(RT) Luo ruotianluo
Waymo Perception SWE. Phd graduate from TTIC.

Waymo Austin

@yuandong-tian
Yuandong Tian yuandong-tian
Research Scientist in Meta AI Research (FAIR)

Facebook

@justdark
DarkScope justdark
Active Learner.

China

@tqchen
Tianqi Chen tqchen
Machine Learning and Systems

CMU, NVIDIA

@junyanz
Jun-Yan Zhu junyanz
Understanding and creating pixels.

Carnegie Mellon University: Pittsburgh, PA

@shelhamer
Evan Shelhamer shelhamer

UBC / Vector Vancouver, BC and SF, CA

@apaszke
Adam Paszke apaszke
Author of PyTorch. Research Scientist @ Google.

@google Berlin, Germany

@s9xie
Saining Xie s9xie
Assistant Professor of Computer Science at NYU Courant

Courant Institute of Mathematical Sciences, New York University NYC

@fmassa
Francisco Massa fmassa

Facebook AI Reseach

@soumith
Soumith Chintala soumith
/\︿╱\ _____________________________ \0_ 0 /╱\╱________________________ \▁︹_/

Meta New York, USA

@karpathy
Andrej karpathy
I like to train Deep Neural Nets on large datasets.

Stanford