Potential-based Shaping in Model-based Reinforcement Learning. - John Asmuth; Michael L. Littman; Robert Zinkov (AAAI, 2008)

Sensitivity analysis for distributed optimization with resource constraints. - Emma Bowring; Zhengyu Yin; Rob Zinkov; Milind Tambe (AAMAS (1), 2009)

Probabilistic Inference by Program Transformation in Hakaru (System Description). - Praveen Narayanan; Jacques Carette; Wren Romano; Chung-chieh Shan; Robert Zinkov (FLOPS, 2016)

Using synthetic data to train neural networks is model-based reasoning. - Tuan Anh Le 001; Atilim Günes Baydin; Robert Zinkov; Frank D. Wood (IJCNN, 2017)

Composing Inference Algorithms as Program Transformations. - Robert Zinkov; Chung-chieh Shan (UAI, 2017)

Faithful Model Inversion Substantially Improves Auto-encoding Variational Inference. - Stefan Webb; Adam Golinski; Robert Zinkov; N. Siddharth 001; Yee Whye Teh; Frank D. Wood (CoRR, 2017)

Querying Word Embeddings for Similarity and Relatedness. - Fatemeh Torabi Asr; Robert Zinkov; Michael N. Jones (NAACL-HLT, 2018)

Faithful Inversion of Generative Models for Effective Amortized Inference. - Stefan Webb; Adam Golinski; Robert Zinkov; Siddharth Narayanaswamy; Tom Rainforth; Yee Whye Teh; Frank Wood (NeurIPS, 2018)

Simulation-Based Inference for Global Health Decisions. - Christian Schröder de Witt; Bradley Gram-Hansen; Nantas Nardelli; Andrew Gambardella; Robert Zinkov; Puneet K. Dokania; N. Siddharth 001; Ana Belen Espinosa-Gonzalez; Ara Darzi; Philip H. S. Torr; Atilim Günes Baydin (CoRR, 2020)

probKanren: A Simple Probabilistic Extension for microKanren. - Robert Zinkov; William E. Byrd (ICLP Workshops, 2021)

Amortized Rejection Sampling in Universal Probabilistic Programming. - Saeid Naderiparizi; Adam Scibior; Andreas Munk 001; Mehrdad Ghadiri; Atilim Gunes Baydin; Bradley J. Gram-Hansen; Christian A. Schröder de Witt; Robert Zinkov; Philip H. S. Torr; Tom Rainforth; Yee Whye Teh; Frank Wood (AISTATS, 2022)

PyMC: a modern, and comprehensive probabilistic programming framework in Python. - Oriol Abril Pla; Virgile Andréani; Colin Carroll; Larry Dong; Christopher Fonnesbeck; Maxim Kochurov; Ravin Kumar; Junpeng Lao; Christian C. Luhmann; Osvaldo A. Martin; Michael Osthege; Ricardo Vieira; et al. (PeerJ Comput. Sci., 2023)

Verified Multi-Step Synthesis using Large Language Models and Monte Carlo Tree Search. - David Brandfonbrener; Sibi Raja; Tarun Prasad; Chloe Loughridge; Jianang Yang; Simon Henniger; William E. Byrd; Robert Zinkov; Nada Amin (CoRR, 2024)

BlackJAX: Composable Bayesian inference in JAX. - Alberto Cabezas; Adrien Corenflos; Junpeng Lao; Rémi Louf; Antoine Carnec; Kaustubh Chaudhari; Reuben Cohn-Gordon; Jeremie Coullon; Wei Deng; Sam Duffield; Gerardo Duràn-Martín; Marcin Elantkowski; et al. (CoRR, 2024)