Andreas Stuhlmüller

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	Sve	Od 2019.
Citati	3801	2958
H-indeks	21	18
i10-indeks	24	23

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Noah D. GoodmanStanford UniversityPotvrđena adresa e-pošte na stanford.edu
Owain EvansAssociate, CHAI, UC BerkeleyPotvrđena adresa e-pošte na philosophy.ox.ac.uk
Joshua B. TenenbaumMITPotvrđena adresa e-pošte na mit.edu
David WingateAssociate professor of Computer Science, Brigham Young UniversityPotvrđena adresa e-pošte na cs.byu.edu
Tomer UllmanAssistant Professor, HarvardPotvrđena adresa e-pošte na fas.harvard.edu
William SaundersOpenAIPotvrđena adresa e-pošte na cs.toronto.edu
Girish SastryIndependentPotvrđena adresa e-pošte na openai.com
Samuel GershmanProfessor, Harvard UniversityPotvrđena adresa e-pošte na fas.harvard.edu
Demi GuoHarvard UniversityPotvrđena adresa e-pošte na college.harvard.edu
Ishita DasguptaSenior Research Scientist, DeepMindPotvrđena adresa e-pošte na google.com
Robert D. HawkinsStanford UniversityPotvrđena adresa e-pošte na stanford.edu
David AbelDeepMind / University of EdinburghPotvrđena adresa e-pošte na deepmind.com
Eli LiflandPotvrđena adresa e-pošte na sage-future.org
Abhishek ThakurHugging FacePotvrđena adresa e-pošte na huggingface.co
Lewis TunstallHugging FacePotvrđena adresa e-pošte na itp.unibe.ch
Michael NoetelUniversity of QueenslandPotvrđena adresa e-pošte na uq.edu.au
Jess RiedelNTT Research - Physics & Informatics LabPotvrđena adresa e-pošte na ntt-research.com
Emmie HineYale UniversityPotvrđena adresa e-pošte na yale.edu
Judith DegenAssociate professor, Stanford University (Linguistics)Potvrđena adresa e-pošte na stanford.edu
Daniel RitchieBrown UniversityPotvrđena adresa e-pošte na brown.edu

Prati

Andreas Stuhlmüller

Elicit

Potvrđena adresa e-pošte na elicit.com - Početna stranica

Language Models Machine Learning Probabilistic Programming Cognitive Science AI


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022	1181	2022
Knowledge and implicature: Modeling language understanding as social cognition ND Goodman, A Stuhlmüller Topics in cognitive science 5 (1), 173-184, 2013	545	2013
The Design and Implementation of Probabilistic Programming Languages ND Goodman, A Stuhlmüller http://dippl.org, 2014	387	2014
Trial without Error: Towards Safe Reinforcement Learning via Human Intervention W Saunders, G Sastry, A Stuhlmueller, O Evans Proceedings of the 17th International Conference on Autonomous Agents and …, 2018	324	2018
Lightweight implementations of probabilistic programming languages via transformational compilation D Wingate, A Stuhlmüller, ND Goodman International Conference on Artificial Intelligence and Statistics, 770-778, 2011	216	2011
Learning the Preferences of Ignorant, Inconsistent Agents O Evans, A Stuhlmüller, ND Goodman Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-2016), 2016	149	2016
Evaluating Compositionality in Sentence Embeddings I Dasgupta, D Guo, A Stuhlmüller, SJ Gershman, ND Goodman arXiv preprint arXiv:1802.04302, 2018	139	2018
Learning Stochastic Inverses A Stuhlmüller, J Taylor, N Goodman Advances in Neural Information Processing Systems, 3048-3056, 2013	127	2013
Reasoning about reasoning by nested conditioning: Modeling theory of mind with probabilistic programs A Stuhlmüller, ND Goodman Cognitive Systems Research 28, 80-99, 2014	95	2014
Agent-Agnostic Human-in-the-Loop Reinforcement Learning D Abel, J Salvatier, A Stuhlmüller, O Evans Future of Interactive Learning Machines Workshop at NIPS 2016, 2016	86	2016
Learning physical parameters from dynamic scenes TD Ullman, A Stuhlmüller, ND Goodman, JB Tenenbaum Cognitive psychology 104, 57-82, 2018	72	2018
RAFT: A Real-World Few-Shot Text Classification Benchmark N Alex, E Lifland, L Tunstall, A Thakur, P Maham, CJ Riedel, E Hine, ... arXiv preprint arXiv:2109.14076, 2021	64	2021
Why do you ask? Good questions provoke informative answers. RXD Hawkins, A Stuhlmüller, J Degen, ND Goodman Proceedings of the 37th Annual Conference of the Cognitive Science Society, 2015	53	2015
Learning physics from dynamical scenes T Ullman, A Stuhlmüller, N Goodman, JB Tenenbaum Proceedings of the 36th Annual Conference of the Cognitive Science Society …, 2014	43*	2014
C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching D Ritchie, A Stuhlmüller, ND Goodman Proceedings of the 19th International Conference on Artificial Intelligence …, 2016	41	2016
Nonstandard Interpretations of Probabilistic Programs for Efficient Inference D Wingate, ND Goodman, A Stuhlmüller, JM Siskind Advances in Neural Information Processing Systems, 2011	41	2011
Learning Structured Generative Concepts A Stuhlmüller, JB Tenenbaum, ND Goodman Proceedings of the Thirty-Second Annual Conference of the Cognitive Science …, 2010	38	2010
Learning the Preferences of Bounded Agents O Evans, A Stuhlmüller, ND Goodman Advances in Neural Information Processing Systems (Bounded Optimality Workshop), 2015	37	2015
A Dynamic Programming Algorithm for Inference in Recursive Probabilistic Programs A Stuhlmüller, ND Goodman Second Statistical Relational AI workshop at UAI 2012 (StaRAI-12), 2012	35	2012
Inducing Probabilistic Programs by Bayesian Program Merging I Hwang, A Stuhlmüller, ND Goodman Arxiv preprint arXiv:1110.5667, 2011	31	2011

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