Andreas Stuhlmüller | DeepAI

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Featured Co-authors

Noah D. Goodman
52 publications
Daniel Ritchie
26 publications
N. Siddharth
26 publications
Ishita Dasgupta
21 publications
David Abel
17 publications
Owain Evans
15 publications
Demi Guo
11 publications
Samuel J. Gershman
10 publications
Robert X. D. Hawkins
5 publications
John Salvatier
4 publications
Irvin Hwang
1 publication

∙ 01/04/2023

Iterated Decomposition: Improving Science Q A by Supervising Reasoning Processes

Language models (LMs) can perform complex reasoning either end-to-end, w...

0 Justin Reppert, et al. ∙

∙ 02/12/2018

Evaluating Compositionality in Sentence Embeddings

An important frontier in the quest for human-like AI is compositional se...

0 Ishita Dasgupta, et al. ∙

∙ 01/15/2017

Agent-Agnostic Human-in-the-Loop Reinforcement Learning

Providing Reinforcement Learning agents with expert advice can dramatica...

0 David Abel, et al. ∙

∙ 09/09/2015

Coarse-to-Fine Sequential Monte Carlo for Probabilistic Programs

Many practical techniques for probabilistic inference require a sequence...

0 Andreas Stuhlmüller, et al. ∙

∙ 09/07/2015

C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching

Lightweight, source-to-source transformation approaches to implementing ...

0 Daniel Ritchie, et al. ∙

∙ 06/15/2012

A Dynamic Programming Algorithm for Inference in Recursive Probabilistic Programs

We describe a dynamic programming algorithm for computing the marginal d...

0 Andreas Stuhlmüller, et al. ∙

∙ 10/25/2011

Inducing Probabilistic Programs by Bayesian Program Merging

This report outlines an approach to learning generative models from data...

0 Irvin Hwang, et al. ∙

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