| Statistical topic models for multi-label document classification TN Rubin, A Chambers, P Smyth, M Steyvers Machine learning 88, 157-208, 2012 | 456 | 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 | 121 | 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 | 94 | 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 | 50 | 2018 |
| Dense distributions from sparse samples: improved Gibbs sampling parameter estimators for LDA Y Papanikolaou, JR Foulds, TN Rubin, G Tsoumakas Journal of Machine Learning Research 18 (62), 1-58, 2017 | 47 | 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 | 35 | 2016 |
| Unsupervised machine learning of topics documented by nurses about hospitalized patients prior to a rapid-response event ZT Korach, KD Cato, SA Collins, MJ Kang, C Knaplund, PC Dykes, ... Applied Clinical Informatics 10 (05), 952-963, 2019 | 23 | 2019 |
| 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 | 13 | 2014 |
| 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 | 11 | 2016 |
| A topic model for movie choices and ratings T Rubin, M Steyvers Proceedings of the 9th International Conference on Cognitive Modeling, 2009 | 11 | 2009 |
| Modeling tag dependencies in tagged documents TN Rubin, UC Irvine, A Holloway, P Smyth, M Steyvers NIPS 2009 Applications for Topic Models Workshop, 2009 | 2 | 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 | 2 | 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 | 1 | 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 | 1 | |
| Classification and Categorization in Machine Learning and Psychology TN Rubin University of California, Irvine, 2012 | | 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 | | 2008 |
Mark SteyversUniversity of California, Irvine在 uci.edu 的电子邮件经过验证
