2008 |
37 | EE | Joshua B. Tenenbaum:
Building Theories of the World: Human and Machine Learning Perspectives.
ILP 2008: 1 |
36 | EE | Noah Goodman,
Vikash K. Mansinghka,
Daniel M. Roy,
Keith Bonawitz,
Joshua B. Tenenbaum:
Church: a language for generative models.
UAI 2008: 220-229 |
35 | EE | Mike Dowman,
Virginia Savova,
Thomas L. Griffiths,
Konrad P. Körding,
Joshua B. Tenenbaum,
Matthew Purver:
A Probabilistic Model of Meetings That Combines Words and Discourse Features.
IEEE Transactions on Audio, Speech & Language Processing 16(7): 1238-1248 (2008) |
2007 |
34 | EE | Michael Frank,
Noah Goodman,
Joshua B. Tenenbaum:
A Bayesian Framework for Cross-Situational Word-Learning.
NIPS 2007 |
33 | EE | Charles Kemp,
Noah Goodman,
Joshua B. Tenenbaum:
Learning and using relational theories.
NIPS 2007 |
32 | EE | Tomoharu Iwata,
Kazumi Saito,
Naonori Ueda,
Sean Stromsten,
Thomas L. Griffiths,
Joshua B. Tenenbaum:
Parametric Embedding for Class Visualization.
Neural Computation 19(9): 2536-2556 (2007) |
2006 |
31 | | Charles Kemp,
Joshua B. Tenenbaum,
Thomas L. Griffiths,
Takeshi Yamada,
Naonori Ueda:
Learning Systems of Concepts with an Infinite Relational Model.
AAAI 2006 |
30 | EE | Matthew Purver,
Konrad P. Körding,
Thomas L. Griffiths,
Joshua B. Tenenbaum:
Unsupervised Topic Modelling for Multi-Party Spoken Discourse.
ACL 2006 |
29 | EE | Daniel M. Roy,
Charles Kemp,
Vikash K. Mansinghka,
Joshua B. Tenenbaum:
Learning annotated hierarchies from relational data.
NIPS 2006: 1185-1192 |
28 | EE | Charles Kemp,
Patrick Shafto,
Allison Berke,
Joshua B. Tenenbaum:
Combining causal and similarity-based reasoning.
NIPS 2006: 681-688 |
27 | EE | Konrad P. Körding,
Joshua B. Tenenbaum:
Causal inference in sensorimotor integration.
NIPS 2006: 737-744 |
26 | EE | Konrad P. Körding,
Joshua B. Tenenbaum,
Reza Shadmehr:
Multiple timescales and uncertainty in motor adaptation.
NIPS 2006: 745-752 |
25 | EE | Vikash K. Mansinghka,
Charles Kemp,
Thomas L. Griffiths,
Joshua B. Tenenbaum:
Structured Priors for Structure Learning.
UAI 2006 |
2005 |
24 | EE | Chris Baker,
Joshua B. Tenenbaum,
Rebecca Saxe:
Bayesian models of human action understanding.
NIPS 2005 |
23 | EE | Mark Steyvers,
Joshua B. Tenenbaum:
The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth.
Cognitive Science 29(1): 41-78 (2005) |
2004 |
22 | EE | Thomas L. Griffiths,
Mark Steyvers,
David M. Blei,
Joshua B. Tenenbaum:
Integrating Topics and Syntax.
NIPS 2004 |
21 | EE | Tomoharu Iwata,
Kazumi Saito,
Naonori Ueda,
Sean Stromsten,
Thomas L. Griffiths,
Joshua B. Tenenbaum:
Parametric Embedding for Class Visualization.
NIPS 2004 |
20 | EE | David M. Sobel,
Joshua B. Tenenbaum,
Alison Gopnik:
Children's causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers.
Cognitive Science 28(3): 303-333 (2004) |
2003 |
19 | EE | Thomas L. Griffiths,
Joshua B. Tenenbaum:
From Algorithmic to Subjective Randomness.
NIPS 2003 |
18 | EE | David M. Blei,
Thomas L. Griffiths,
Michael I. Jordan,
Joshua B. Tenenbaum:
Hierarchical Topic Models and the Nested Chinese Restaurant Process.
NIPS 2003 |
17 | EE | Charles Kemp,
Thomas L. Griffiths,
Sean Stromsten,
Joshua B. Tenenbaum:
Semi-Supervised Learning with Trees.
NIPS 2003 |
16 | EE | William T. Freeman,
Joshua B. Tenenbaum,
Egon C. Pasztor:
Learning style translation for the lines of a drawing.
ACM Trans. Graph. 22(1): 33-46 (2003) |
15 | EE | Mark Steyvers,
Joshua B. Tenenbaum,
Eric-Jan Wagenmakers,
Ben Blum:
Inferring causal networks from observations and interventions.
Cognitive Science 27(3): 453-489 (2003) |
2002 |
14 | EE | Joshua B. Tenenbaum,
Thomas L. Griffiths:
Theory-Based Causal Inference.
NIPS 2002: 35-42 |
13 | EE | Neville E. Sanjana,
Joshua B. Tenenbaum:
Bayesian Models of Inductive Generalization.
NIPS 2002: 51-58 |
12 | EE | David Danks,
Thomas L. Griffiths,
Joshua B. Tenenbaum:
Dynamical Causal Learning.
NIPS 2002: 67-74 |
11 | EE | Vin de Silva,
Joshua B. Tenenbaum:
Global Versus Local Methods in Nonlinear Dimensionality Reduction.
NIPS 2002: 705-712 |
2001 |
10 | EE | Thomas L. Griffiths,
Joshua B. Tenenbaum:
Using Vocabulary Knowledge in Bayesian Multinomial Estimation.
NIPS 2001: 1385-1392 |
2000 |
9 | | Joshua B. Tenenbaum,
Thomas L. Griffiths:
Structure Learning in Human Causal Induction.
NIPS 2000: 59-65 |
8 | | Joshua B. Tenenbaum,
William T. Freeman:
Separating Style and Content with Bilinear Models.
Neural Computation 12(6): 1247-1283 (2000) |
1999 |
7 | EE | Joshua B. Tenenbaum:
Rules and Similarity in Concept Learning.
NIPS 1999: 59-65 |
1998 |
6 | EE | Joshua B. Tenenbaum:
Bayesian Modeling of Human Concept Learning.
NIPS 1998: 59-68 |
1997 |
5 | EE | William T. Freeman,
Joshua B. Tenenbaum:
Learning bilinear models for two-factor problems in vision.
CVPR 1997: 554-560 |
4 | | Joshua B. Tenenbaum:
Mapping a Manifold of Perceptual Observations.
NIPS 1997 |
1996 |
3 | EE | Joshua B. Tenenbaum,
William T. Freeman:
Separating Style and Content.
NIPS 1996: 662-668 |
1995 |
2 | EE | Joshua B. Tenenbaum:
Learning the Structure of Similarity.
NIPS 1995: 3-9 |
1994 |
1 | EE | Joshua B. Tenenbaum,
Emanuel Todorov:
Factorial Learning by Clustering Features.
NIPS 1994: 561-568 |