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Joshua B. Tenenbaum: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Charles Kemp, Joshua B. Tenenbaum, Thomas L. Griffiths, Takeshi Yamada, Naonori Ueda
    Learning Systems of Concepts with an Infinite Relational Model. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  2. Matthew Purver, Konrad P. Körding, Thomas L. Griffiths, Joshua B. Tenenbaum
    Unsupervised Topic Modelling for Multi-Party Spoken Discourse. [Citation Graph (0, 0)][DBLP]
    ACL, 2006, pp:- [Conf]
  3. William T. Freeman, Joshua B. Tenenbaum
    Learning bilinear models for two-factor problems in vision. [Citation Graph (0, 0)][DBLP]
    CVPR, 1997, pp:554-560 [Conf]
  4. Chris Baker, Joshua B. Tenenbaum, Rebecca Saxe
    Bayesian models of human action understanding. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  5. David M. Blei, Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum
    Hierarchical Topic Models and the Nested Chinese Restaurant Process. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  6. David Danks, Thomas L. Griffiths, Joshua B. Tenenbaum
    Dynamical Causal Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:67-74 [Conf]
  7. Thomas L. Griffiths, Mark Steyvers, David M. Blei, Joshua B. Tenenbaum
    Integrating Topics and Syntax. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  8. Thomas L. Griffiths, Joshua B. Tenenbaum
    Using Vocabulary Knowledge in Bayesian Multinomial Estimation. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:1385-1392 [Conf]
  9. Thomas L. Griffiths, Joshua B. Tenenbaum
    From Algorithmic to Subjective Randomness. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  10. Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths, Joshua B. Tenenbaum
    Parametric Embedding for Class Visualization. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  11. Charles Kemp, Thomas L. Griffiths, Sean Stromsten, Joshua B. Tenenbaum
    Semi-Supervised Learning with Trees. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  12. Neville E. Sanjana, Joshua B. Tenenbaum
    Bayesian Models of Inductive Generalization. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:51-58 [Conf]
  13. Vin de Silva, Joshua B. Tenenbaum
    Global Versus Local Methods in Nonlinear Dimensionality Reduction. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:705-712 [Conf]
  14. Joshua B. Tenenbaum
    Learning the Structure of Similarity. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:3-9 [Conf]
  15. Joshua B. Tenenbaum
    Mapping a Manifold of Perceptual Observations. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  16. Joshua B. Tenenbaum
    Bayesian Modeling of Human Concept Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:59-68 [Conf]
  17. Joshua B. Tenenbaum
    Rules and Similarity in Concept Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:59-65 [Conf]
  18. Joshua B. Tenenbaum, William T. Freeman
    Separating Style and Content. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:662-668 [Conf]
  19. Joshua B. Tenenbaum, Thomas L. Griffiths
    Structure Learning in Human Causal Induction. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:59-65 [Conf]
  20. Joshua B. Tenenbaum, Thomas L. Griffiths
    Theory-Based Causal Inference. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:35-42 [Conf]
  21. Joshua B. Tenenbaum, Emanuel Todorov
    Factorial Learning by Clustering Features. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:561-568 [Conf]
  22. David M. Sobel, Joshua B. Tenenbaum, Alison Gopnik
    Children's causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers. [Citation Graph (0, 0)][DBLP]
    Cognitive Science, 2004, v:28, n:3, pp:303-333 [Journal]
  23. Mark Steyvers, Joshua B. Tenenbaum
    The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth. [Citation Graph (0, 0)][DBLP]
    Cognitive Science, 2005, v:29, n:1, pp:41-78 [Journal]
  24. Mark Steyvers, Joshua B. Tenenbaum, Eric-Jan Wagenmakers, Ben Blum
    Inferring causal networks from observations and interventions. [Citation Graph (0, 0)][DBLP]
    Cognitive Science, 2003, v:27, n:3, pp:453-489 [Journal]
  25. Joshua B. Tenenbaum, William T. Freeman
    Separating Style and Content with Bilinear Models. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:6, pp:1247-1283 [Journal]
  26. William T. Freeman, Joshua B. Tenenbaum, Egon C. Pasztor
    Learning style translation for the lines of a drawing. [Citation Graph (0, 0)][DBLP]
    ACM Trans. Graph., 2003, v:22, n:1, pp:33-46 [Journal]
  27. Daniel M. Roy, Charles Kemp, Vikash K. Mansinghka, Joshua B. Tenenbaum
    Learning annotated hierarchies from relational data. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1185-1192 [Conf]
  28. Charles Kemp, Patrick Shafto, Allison Berke, Joshua B. Tenenbaum
    Combining causal and similarity-based reasoning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:681-688 [Conf]
  29. Konrad P. Körding, Joshua B. Tenenbaum
    Causal inference in sensorimotor integration. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:737-744 [Conf]
  30. Konrad P. Körding, Joshua B. Tenenbaum, Reza Shadmehr
    Multiple timescales and uncertainty in motor adaptation. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:745-752 [Conf]
  31. Vikash K. Mansinghka, Charles Kemp, Thomas L. Griffiths, Joshua B. Tenenbaum
    Structured Priors for Structure Learning. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]

  32. Building Theories of the World: Human and Machine Learning Perspectives. [Citation Graph (, )][DBLP]


  33. Learning and using relational theories. [Citation Graph (, )][DBLP]


  34. A Bayesian Framework for Cross-Situational Word-Learning. [Citation Graph (, )][DBLP]


  35. Church: a language for generative models. [Citation Graph (, )][DBLP]


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