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David M Blei

Showing results (11-20 of 21) with videos related to

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Neuroimage|May 10, 2011
A topographic latent source model for fMRI dataSamuel J Gershman, David M Blei, Francisco Pereira, et al.
Plos One|May 9, 2014
Topographic factor analysis: a Bayesian model for inferring brain networks from neural dataJeremy R Manning, Rajesh Ranganath, Kenneth A Norman, et al.
Journal of Machine Learning Research : JMLR|June 25, 2011
Mixed Membership Stochastic BlockmodelsEdoardo M Airoldi, David M Blei, Stephen E Fienberg, et al.
Plos One|April 10, 2018
Readmission prediction via deep contextual embedding of clinical conceptsCao Xiao, Tengfei Ma, Adji B Dieng, et al.
Neuroimage|May 6, 2014
Decomposing spatiotemporal brain patterns into topographic latent sourcesSamuel J Gershman, David M Blei, Kenneth A Norman, et al.
Journal of Biomedical Informatics|September 15, 2022
Adjusting for indirectly measured confounding using large-scale propensity scoreLinying Zhang, Yixin Wang, Martijn J Schuemie, et al.
Proceedings of the National Academy of Sciences of the United States of America|March 14, 2018
Measuring discursive influence across scholarshipAaron Gerow, Yuening Hu, Jordan Boyd-Graber, et al.
Journal of Biomedical Informatics|May 23, 2024
Causal fairness assessment of treatment allocation with electronic health recordsLinying Zhang, Lauren R Richter, Yixin Wang, et al.
Biostatistics (Oxford, England)|January 8, 2021
Dose-response modeling in high-throughput cancer drug screenings: an end-to-end approachWesley Tansey, Kathy Li, Haoran Zhang, et al.
Neuroimage|February 16, 2018
A probabilistic approach to discovering dynamic full-brain functional connectivity patternsJeremy R Manning, Xia Zhu, Theodore L Willke, et al.
Pageof 3

Showing results (11-20 of 21) with videos related to

Sort By:
Pageof 3
Neuroimage|May 10, 2011
A topographic latent source model for fMRI dataSamuel J Gershman, David M Blei, Francisco Pereira, et al.
Plos One|May 9, 2014
Topographic factor analysis: a Bayesian model for inferring brain networks from neural dataJeremy R Manning, Rajesh Ranganath, Kenneth A Norman, et al.
Journal of Machine Learning Research : JMLR|June 25, 2011
Mixed Membership Stochastic BlockmodelsEdoardo M Airoldi, David M Blei, Stephen E Fienberg, et al.
Plos One|April 10, 2018
Readmission prediction via deep contextual embedding of clinical conceptsCao Xiao, Tengfei Ma, Adji B Dieng, et al.
Neuroimage|May 6, 2014
Decomposing spatiotemporal brain patterns into topographic latent sourcesSamuel J Gershman, David M Blei, Kenneth A Norman, et al.
Journal of Biomedical Informatics|September 15, 2022
Adjusting for indirectly measured confounding using large-scale propensity scoreLinying Zhang, Yixin Wang, Martijn J Schuemie, et al.
Proceedings of the National Academy of Sciences of the United States of America|March 14, 2018
Measuring discursive influence across scholarshipAaron Gerow, Yuening Hu, Jordan Boyd-Graber, et al.
Journal of Biomedical Informatics|May 23, 2024
Causal fairness assessment of treatment allocation with electronic health recordsLinying Zhang, Lauren R Richter, Yixin Wang, et al.
Biostatistics (Oxford, England)|January 8, 2021
Dose-response modeling in high-throughput cancer drug screenings: an end-to-end approachWesley Tansey, Kathy Li, Haoran Zhang, et al.
Neuroimage|February 16, 2018
A probabilistic approach to discovering dynamic full-brain functional connectivity patternsJeremy R Manning, Xia Zhu, Theodore L Willke, et al.
Pageof 3