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All publications by Joshua B. Tenenbaum
authors venues years



Learning to Learn with Compound HD Models
Antonio Torralba, Joshua B. Tenenbaum and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 24, 2011


Nonparametric Bayesian Policy Priors for Reinforcement Learning
Finale Doshi-velez, David Wingate, Nicholas Roy and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 23, 2010


Dynamic Infinite Relational Model for Time-varying Relational Data Analysis
Katsuhiko Ishiguro, Tomoharu Iwata, Naonori Ueda and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 23, 2010


Help or Hinder: Bayesian Models of Social Goal Inference
Tomer Ullman, Chris Baker, Owen Macindoe, Owain Evans, Noah Goodman and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 22, 2009


Perceptual Multistability as Markov Chain Monte Carlo Inference
Samuel Gershman, Ed Vul and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 22, 2009


Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model
Edward Vul, Michael C. Frank, Joshua B. Tenenbaum and George Alvarez
Advances in Neural Information Processing Systems 22, 2009


Modelling Relational Data using Bayesian Clustered Tensor Factorization
Ilya Sutskever, Joshua B. Tenenbaum and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 22, 2009


Exact and Approximate Sampling by Systematic Stochastic Search
Vikash K. Mansinghka, Daniel M. Roy, Eric Jonas and Joshua B. Tenenbaum
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


A Bayesian Framework for Cross-Situational Word-Learning
Noah Goodman, Joshua B. Tenenbaum and Michael J. Black
Advances in Neural Information Processing Systems 20, 2007


Learning and using relational theories
Charles Kemp, Noah Goodman and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 20, 2007


AClass: A simple, online, parallelizable algorithm for probabilistic classification
Vikash K. Mansinghka, Daniel M. Roy, Ryan Rifkin and Joshua B. Tenenbaum
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Combining causal and similarity-based reasoning
Charles Kemp, Patrick Shafto, Allison Berke and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 19, 2006


Learning annotated hierarchies from relational data
Daniel M. Roy, Charles Kemp, Vikash K. Mansinghka and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 19, 2006


Multiple timescales and uncertainty in motor adaptation
Konrad P. Körding, Joshua B. Tenenbaum and Reza Shadmehr
Advances in Neural Information Processing Systems 19, 2006


Causal inference in sensorimotor integration
Konrad P. Körding and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 19, 2006


Bayesian models of human action understanding
Chris Baker, Rebecca Saxe and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 18, 2005


Integrating Topics and Syntax
Thomas L. Griffiths, Mark Steyvers, David M. Blei and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 17, 2004


Parametric Embedding for Class Visualization
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 17, 2004


From Algorithmic to Subjective Randomness
Thomas L. Griffiths and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 16, 2003


Semi-Supervised Learning with Trees
Charles Kemp, Thomas L. Griffiths, Sean Stromsten and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 16, 2003


Hierarchical Topic Models and the Nested Chinese Restaurant Process
Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum and David M. Blei
Advances in Neural Information Processing Systems 16, 2003


Dynamical Causal Learning
David Danks, Thomas L. Griffiths and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 15, 2002


Bayesian Models of Inductive Generalization
Neville E. Sanjana and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 15, 2002


Theory-Based Causal Inference
Joshua B. Tenenbaum and Thomas L. Griffiths
Advances in Neural Information Processing Systems 15, 2002


Global Versus Local Methods in Nonlinear Dimensionality Reduction
Vin D. Silva and Joshua B. Tenenbaum
Advances in Neural Information Processing Systems 15, 2002