Gen: a general-purpose probabilistic programming system with programmable inference MF Cusumano-Towner, FA Saad, AK Lew, VK Mansinghka
Proceedings of the 40th ACM SIGPLAN Conference on Programming Language …, 2019
237 2019 From word models to world models: Translating from natural language to the probabilistic language of thought L Wong, G Grand, AK Lew, ND Goodman, VK Mansinghka, J Andreas, ...
arXiv preprint arXiv:2306.12672, 2023
109 * 2023 Trace types and denotational semantics for sound programmable inference in probabilistic languages AK Lew, MF Cusumano-Towner, B Sherman, M Carbin, VK Mansinghka
Proceedings of the ACM on Programming Languages 4 (POPL), 1-32, 2020
52 2020 Few-shot Bayesian imitation learning with logical program policies T Silver, KR Allen, AK Lew, LP Kaelbling, J Tenenbaum
AAAI, 10251-10258, 2020
51 2020 PClean: Bayesian data cleaning at scale with domain-specific probabilistic programming AK Lew, M Agrawal, D Sontag, VK Mansinghka
International Conference on Artificial Intelligence and Statistics, 1927-1935, 2021
33 2021 Sequential Monte Carlo steering of large language models using probabilistic programs AK Lew, T Zhi-Xuan, G Grand, VK Mansinghka
arXiv preprint arXiv:2306.03081, 2023
30 2023 ADEV: Sound automatic differentiation of expected values of probabilistic programs AK Lew*, M Huot*, S Staton, VK Mansinghka
Proceedings of the ACM on Programming Languages 7 (POPL), 121-153, 2023
25 2023 Automating involutive MCMC using probabilistic and differentiable programming M Cusumano-Towner, AK Lew, VK Mansinghka
arXiv preprint arXiv:2007.09871, 2020
20 2020 SMCP3: Sequential Monte Carlo with probabilistic program proposals AK Lew*, G Matheos*, T Zhi-Xuan, M Ghavamizadeh, N Gothoskar, ...
International Conference on Artificial Intelligence and Statistics, 7061-7088, 2023
19 2023 Leveraging unstructured statistical knowledge in a probabilistic language of thought AK Lew, MH Tessler, VK Mansinghka, JB Tenenbaum
Proceedings of the Annual Conference of the Cognitive Science Society, 2020
15 2020 Recursive Monte Carlo and variational inference with auxiliary variables AK Lew, M Cusumano-Towner, VK Mansinghka
The 38th Conference on Uncertainty in Artificial Intelligence, 2022
13 2022 Probabilistic programming with stochastic probabilities AK Lew, M Ghavamizadeh, MC Rinard, VK Mansinghka
Proceedings of the ACM on Programming Languages 7 (PLDI), 1708-1732, 2023
10 2023 M Huot*, AK Lew*, VK Mansinghka, S Staton
Logic in Computer Science (LICS 2023), 2023
10 2023 Bayesian causal inference via probabilistic program synthesis S Witty*, AK Lew*, D Jensen, V Mansinghka
arXiv preprint arXiv:1910.14124, 2019
9 2019 Differentiating Metropolis-Hastings to optimize intractable densities G Arya, R Seyer, F Schäfer, AK Lew, M Huot, VK Mansinghka, ...
Differentiable Almost Everything (ICML 2023 workshop), 2023
8 2023 Towards denotational semantics of AD for higher-order, recursive, probabilistic languages AK Lew, M Huot, VK Mansinghka
NeurIPS Differentiable Programming Workshop (2021), 2021
6 * 2021 Few-shot bayesian imitation learning with logic over programs T Silver, KR Allen, AK Lew, L Kaelbling, J Tenenbaum
arXiv preprint arXiv:1904.06317, 2019
6 2019 Transforming worlds: automated involutive MCMC for open-universe probabilistic models G Matheos*, AK Lew*, M Ghavamizadeh, S Russell, ...
Advances in Approximate Bayesian Inference, 2021
4 2021 Syntactic and semantic control of large language models via sequential Monte Carlo J Loula, B LeBrun, L Du, B Lipkin, C Pasti, G Grand, T Liu, Y Emara, ...
The Thirteenth International Conference on Learning Representations, 2025
2 * 2025 Probabilistic programming with programmable variational inference MCR Becker*, AK Lew*, X Wang, M Ghavami, M Huot, MC Rinard, ...
Proceedings of the ACM on Programming Languages 8 (PLDI), 2123-2147, 2024
2 2024 
Vikash K. MansinghkaMIT, Probabilistic Computing ProjectEmail verificata su mit.edu
