Joshua B. Tenenbaum

	2008
37		Joshua B. Tenenbaum: Building Theories of the World: Human and Machine Learning Perspectives. ILP 2008: 1
36		Noah Goodman, Vikash K. Mansinghka, Daniel M. Roy, Keith Bonawitz, Joshua B. Tenenbaum: Church: a language for generative models. UAI 2008: 220-229
35		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		Michael Frank, Noah Goodman, Joshua B. Tenenbaum: A Bayesian Framework for Cross-Situational Word-Learning. NIPS 2007
33		Charles Kemp, Noah Goodman, Joshua B. Tenenbaum: Learning and using relational theories. NIPS 2007
32		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		Matthew Purver, Konrad P. Körding, Thomas L. Griffiths, Joshua B. Tenenbaum: Unsupervised Topic Modelling for Multi-Party Spoken Discourse. ACL 2006
29		Daniel M. Roy, Charles Kemp, Vikash K. Mansinghka, Joshua B. Tenenbaum: Learning annotated hierarchies from relational data. NIPS 2006: 1185-1192
28		Charles Kemp, Patrick Shafto, Allison Berke, Joshua B. Tenenbaum: Combining causal and similarity-based reasoning. NIPS 2006: 681-688
27		Konrad P. Körding, Joshua B. Tenenbaum: Causal inference in sensorimotor integration. NIPS 2006: 737-744
26		Konrad P. Körding, Joshua B. Tenenbaum, Reza Shadmehr: Multiple timescales and uncertainty in motor adaptation. NIPS 2006: 745-752
25		Vikash K. Mansinghka, Charles Kemp, Thomas L. Griffiths, Joshua B. Tenenbaum: Structured Priors for Structure Learning. UAI 2006
	2005
24		Chris Baker, Joshua B. Tenenbaum, Rebecca Saxe: Bayesian models of human action understanding. NIPS 2005
23		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		Thomas L. Griffiths, Mark Steyvers, David M. Blei, Joshua B. Tenenbaum: Integrating Topics and Syntax. NIPS 2004
21		Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths, Joshua B. Tenenbaum: Parametric Embedding for Class Visualization. NIPS 2004
20		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		Thomas L. Griffiths, Joshua B. Tenenbaum: From Algorithmic to Subjective Randomness. NIPS 2003
18		David M. Blei, Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum: Hierarchical Topic Models and the Nested Chinese Restaurant Process. NIPS 2003
17		Charles Kemp, Thomas L. Griffiths, Sean Stromsten, Joshua B. Tenenbaum: Semi-Supervised Learning with Trees. NIPS 2003
16		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		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		Joshua B. Tenenbaum, Thomas L. Griffiths: Theory-Based Causal Inference. NIPS 2002: 35-42
13		Neville E. Sanjana, Joshua B. Tenenbaum: Bayesian Models of Inductive Generalization. NIPS 2002: 51-58
12		David Danks, Thomas L. Griffiths, Joshua B. Tenenbaum: Dynamical Causal Learning. NIPS 2002: 67-74
11		Vin de Silva, Joshua B. Tenenbaum: Global Versus Local Methods in Nonlinear Dimensionality Reduction. NIPS 2002: 705-712
	2001
10		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		Joshua B. Tenenbaum: Rules and Similarity in Concept Learning. NIPS 1999: 59-65
	1998
6		Joshua B. Tenenbaum: Bayesian Modeling of Human Concept Learning. NIPS 1998: 59-68
	1997
5		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		Joshua B. Tenenbaum, William T. Freeman: Separating Style and Content. NIPS 1996: 662-668
	1995
2		Joshua B. Tenenbaum: Learning the Structure of Similarity. NIPS 1995: 3-9
	1994
1		Joshua B. Tenenbaum, Emanuel Todorov: Factorial Learning by Clustering Features. NIPS 1994: 561-568

Coauthor Index

1	Chris Baker	[24]
2	Allison Berke	[28]
3	David M. Blei	[18] [22]
4	Ben Blum	[15]
5	Keith Bonawitz	[36]
6	David Danks	[12]
7	Mike Dowman	[35]
8	Michael Frank	[34]
9	William T. Freeman	[3] [5] [8] [16]
10	Noah Goodman	[33] [34] [36]
11	Alison Gopnik	[20]
12	Thomas L. Griffiths	[9] [10] [12] [14] [17] [18] [19] [21] [22] [25] [30] [31] [32] [35]
13	Tomoharu Iwata	[21] [32]
14	Michael I. Jordan	[18]
15	Charles Kemp	[17] [25] [28] [29] [31] [33]
16	Konrad P. Körding	[26] [27] [30] [35]
17	Vikash K. Mansinghka	[25] [29] [36]
18	Egon C. Pasztor	[16]
19	Matthew Purver	[30] [35]
20	Daniel M. Roy	[29] [36]
21	Kazumi Saito	[21] [32]
22	Neville E. Sanjana	[13]
23	Virginia Savova	[35]
24	Rebecca Saxe	[24]
25	Reza Shadmehr	[26]
26	Patrick Shafto	[28]
27	Vin de Silva	[11]
28	David M. Sobel	[20]
29	Mark Steyvers	[15] [22] [23]
30	Sean Stromsten	[17] [21] [32]
31	Emanuel Todorov	[1]
32	Naonori Ueda	[21] [31] [32]
33	Eric-Jan Wagenmakers	[15]
34	Takeshi Yamada	[31]

Colors in the list of coauthors