June 22, 2019
HackPPL is a probabilistic programming language (PPL) built within the Hack programming language. Its universal inference engine allows developers to perform inference across a diverse set of models expressible in arbitrary Hack code. Through language-level extensions and direct integration with developer tools, HackPPL aims to bridge the gap between domain-specific and embedded PPLs. This paper overviews the design and implementation choices for the HackPPL toolchain and presents findings by applying it to a representative problem faced by social media companies.
October 19, 2026
Muse Glimmer team
October 19, 2026
October 14, 2026
Arturo Loazia-Bonilla
October 14, 2026
October 14, 2026
Daniel Kim
October 14, 2026
October 14, 2026
Paddy Ssentongo
October 14, 2026
October 31, 2019
Peng-Jen Chen, Jiajun Shen, Matt Le, Vishrav Chaudhary, Ahmed El-Kishky, Guillaume Wenzek, Myle Ott, Marc’Aurelio Ranzato
October 31, 2019
October 27, 2019
Zhuoyuan Chen, Demi Guo, Tong Xiao, Saining Xie, Xinlei Chen, Haonan Yu, Jonathan Gray, Kavya Srinet, Haoqi Fan, Jerry Ma, Charles R. Qi, Shubham Tulsiani, Arthur Szlam, Larry Zitnick
October 27, 2019
April 25, 2020
Yilun Du, Joshua Meier, Jerry Ma, Rob Fergus, Alexander Rives
April 25, 2020
June 11, 2019
Yuandong Tian, Jerry Ma, Qucheng Gong, Shubho Sengupta, Zhuoyuan Chen, James Pinkerton, Larry Zitnick
June 11, 2019
