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
201 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
42 2023 Few-shot Bayesian imitation learning with logical program policies T Silver, KR Allen, AK Lew, LP Kaelbling, J Tenenbaum
AAAI, 10251-10258, 2020
41 * 2020 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
39 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
22 2021 Automating involutive MCMC using probabilistic and differentiable programming M Cusumano-Towner, AK Lew, VK Mansinghka
arXiv preprint arXiv:2007.09871, 2020
19 2020 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
16 2023 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
10 2023 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
10 2022 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
9 2023 Bayesian causal inference via probabilistic program synthesis S Witty*, AK Lew*, D Jensen, V Mansinghka
arXiv preprint arXiv:1910.14124, 2019
9 2019 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
8 2020 PAP spaces: Reasoning denotationally about higher-order, recursive probabilistic and differentiable programsM Huot*, AK Lew*, VK Mansinghka, S Staton
Logic in Computer Science (LICS 2023), 2023
6 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 Transforming worlds: automated involutive MCMC for open-universe probabilistic models G Matheos*, AK Lew*, M Ghavamizadeh, S Russell, ...
Advances in Approximate Bayesian Inference, 2021
3 2021 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
2 2023 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
2 2023 What do posterior distributions of probabilistic programs look like? M Huot*, AK Lew*, V Mansinghka, S Staton
Languages for Inference (LAFI), 2023
1 2023