Semisupervised Learning on Heterogeneous Graphs and its Applications to Facebook News Feed. - Cheng Ju; James Li; Bram Wasti; Shengbo Guo (CoRR, 2018)

Machine Learning at Facebook: Understanding Inference at the Edge. - Carole-Jean Wu; David Brooks 001; Kevin Chen; Douglas Chen; Sy Choudhury; Marat Dukhan; Kim M. Hazelwood; Eldad Isaac; Yangqing Jia; Bill Jia; Tommer Leyvand; Hao Lu; et al. (HPCA, 2019)

Q-gym: An Equality Saturation Framework for DNN Inference Exploiting Weight Repetition. - Cheng Fu 002; Hanxian Huang; Bram Wasti; Chris Cummins; Riyadh Baghdadi; Kim M. Hazelwood; Yuandong Tian; Jishen Zhao; Hugh Leather (PACT, 2022)

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. - Chris Cummins; Bram Wasti; Jiadong Guo; Brandon Cui; Jason Ansel; Sahir Gomez; Somya Jain; Jia Liu; Olivier Teytaud; Benoit Steiner; Yuandong Tian; Hugh Leather (CGO, 2022)

LoopStack: a Lightweight Tensor Algebra Compiler Stack. - Bram Wasti; José Pablo Cambronero; Benoit Steiner; Hugh Leather; Aleksandar Zlateski (CoRR, 2022)

LoopTune: Optimizing Tensor Computations with Reinforcement Learning. - Dejan Grubisic; Bram Wasti; Chris Cummins; John M. Mellor-Crummey; Aleksandar Zlateski (CoRR, 2023)

LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding. - Mostafa Elhoushi; Akshat Shrivastava; Diana Liskovich; Basil Hosmer; Bram Wasti; Liangzhen Lai; Anas Mahmoud 002; Bilge Acun; Saurabh Agarwal; Ahmed Roman; Ahmed A Aly; Beidi Chen; et al. (ACL (1), 2024)