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Alexander K. Lew
Alexander K. Lew
Graduate student, MIT
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
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
2062019
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
492023
Few-shot Bayesian imitation learning with logical program policies
T Silver, KR Allen, AK Lew, LP Kaelbling, J Tenenbaum
AAAI, 10251-10258, 2020
43*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
402020
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
232021
Automating involutive MCMC using probabilistic and differentiable programming
M Cusumano-Towner, AK Lew, VK Mansinghka
arXiv preprint arXiv:2007.09871, 2020
192020
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
182023
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
122023
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
102023
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
102022
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
92020
Bayesian causal inference via probabilistic program synthesis
S Witty*, AK Lew*, D Jensen, V Mansinghka
arXiv preprint arXiv:1910.14124, 2019
92019
PAP spaces: Reasoning denotationally about higher-order, recursive probabilistic and differentiable programs
M Huot*, AK Lew*, VK Mansinghka, S Staton
Logic in Computer Science (LICS 2023), 2023
72023
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
42021
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
32023
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
22023
What do posterior distributions of probabilistic programs look like?
M Huot*, AK Lew*, V Mansinghka, S Staton
Languages for Inference (LAFI), 2023
12023
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