3DP3: 3D Scene Perception via Probabilistic Programming. - Nishad Gothoskar; Marco F. Cusumano-Towner; Ben Zinberg; Matin Ghavamizadeh; Falk Pollok; Austin Garrett; Josh Tenenbaum 001; Dan Gutfreund; Vikash K. Mansinghka (NeurIPS, 2021)

SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals. - Alexander K. Lew; George Matheos; Tan Zhi-Xuan; Matin Ghavamizadeh; Nishad Gothoskar; Stuart Russell 001; Vikash K. Mansinghka (AISTATS, 2023)

Bayes3D: fast learning and inference in structured generative models of 3D objects and scenes. - Nishad Gothoskar; Matin Ghavami; Eric Li; Aidan Curtis; Michael Noseworthy; Karen Chung; Brian Patton; William T. Freeman; Joshua B. Tenenbaum; Mirko Klukas; Vikash K. Mansinghka (CoRR, 2023)

Probabilistic Programming with Stochastic Probabilities. - Alexander K. Lew; Matin Ghavamizadeh; Martin C. Rinard; Vikash K. Mansinghka (Proc. ACM Program. Lang., 2023)

Probabilistic Programming with Programmable Variational Inference. - McCoy R. Becker; Alexander K. Lew; Xiaoyan Wang; Matin Ghavami; Mathieu Huot; Martin C. Rinard; Vikash K. Mansinghka (Proc. ACM Program. Lang., 2024)

GenSQL: A Probabilistic Programming System for Querying Generative Models of Database Tables. - Mathieu Huot; Matin Ghavami; Alexander K. Lew; Ulrich Schaechtle; Cameron E. Freer; Zane Shelby; Martin C. Rinard; Feras A. Saad; Vikash K. Mansinghka (Proc. ACM Program. Lang., 2024)