Timothy Rubin
Cited by
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Statistical topic models for multi-label document classification
TN Rubin, A Chambers, P Smyth, M Steyvers
Machine learning 88, 157-208, 2012
Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition
TN Rubin, O Koyejo, KJ Gorgolewski, MN Jones, RA Poldrack, T Yarkoni
PLoS computational biology 13 (10), e1005649, 2017
Topic models: a novel method for modeling couple and family text data.
DC Atkins, TN Rubin, M Steyvers, MA Doeden, BR Baucom, ...
Journal of family psychology 26 (5), 816, 2012
Evidence of disturbances of deep levels of semantic cohesion within personal narratives in schizophrenia
JA Willits, T Rubin, MN Jones, KS Minor, PH Lysaker
Schizophrenia research 197, 365-369, 2018
Dense distributions from sparse samples: improved Gibbs sampling parameter estimators for LDA
Y Papanikolaou, JR Foulds, TN Rubin, G Tsoumakas
The Journal of Machine Learning Research 18 (1), 2058-2115, 2017
Graph‐theoretic properties of networks based on word association norms: implications for models of lexical semantic memory
TM Gruenenfelder, G Recchia, T Rubin, MN Jones
Cognitive science 40 (6), 1460-1495, 2016
Generalized correspondence-LDA models (GC-LDA) for identifying functional regions in the brain
T Rubin, OO Koyejo, MN Jones, T Yarkoni
Advances in neural information processing systems 29, 2016
A topic model for movie choices and ratings
T Rubin, M Steyvers
Proceedings of International Conference on Cognitive Model, 2009
Organizing the space and behavior of semantic models
TN Rubin, B Kievit-Kylar, JA Willits, MN Jones
CogSci... Annual Conference of the Cognitive Science Society. Cognitive …, 2014
Modeling tag dependencies in tagged documents
TN Rubin, UC Irvine, A Holloway, P Smyth, M Steyvers
NIPS 2009 Applications for Topic Models Workshop, 2009
Spatiotemporal dynamics of the perception of dot displays
TN Rubin, CF Chubb, CE Wright, SA Wong, G Sperling
Journal of Vision 8 (6), 282-282, 2008
A model of concept generalization and feature representation in hierarchies
T Rubin, M Zeigenfuze, M Steyvers
Proceedings of the Annual Meeting of the Cognitive Science Society 33 (33), 2011
Hierarchical Bayesian Modeling of Individual Differences in Texture Discrimination
TN Rubin, MD Lee, CF Chubb
Proceedings of the 30th Annual Conference of the Cognitive Science Society, 0
Classification and Categorization in Machine Learning and Psychology
TN Rubin
University of California, Irvine, 2012
Binary versus graded filters for selectively attending to dots of different contrasts
SA Drew, CF Chubb, T Ehrlich, T Rubin, G Sperling
Journal of Vision 8 (6), 881-881, 2008
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