Scaling and Generalizing Approximate Bayesian Inference
Friday, September 13, 2019
3:30 pm - 4:30 pm
David Blei, Columbia University
Causal inference under spillover and contagion: structural versus agnostic methods
Friday, September 20, 2019
3:30 pm - 4:30 pm
Forrest Crawford, Yale School of Public Health
PageRank on Directed Complex Networks
Friday, September 27, 2019
3:30 pm - 4:30 pm
Mariana Olvero-Cravioto, UNC
Markov-Modulated Hawkes Processes for Sporadic and Bursty Event Occurrences
Friday, October 04, 2019
3:30 pm - 4:30 pm
Dr. Tian Zheng, Columbia University
Spiked Laplacian Graphs - harnessing the spectral graph theory in the Bayesian framework
Friday, October 11, 2019
3:30 pm - 4:30 pm
Leo Duan, University of Florida
Bayesian Categorical Matrix Factorization via Double Feature Allocation
Friday, October 18, 2019
3:30 pm - 4:30 pm
Peter Mueller, University of Texas - Austin
Sparsity selection in high-dimensional Bayesian vector autoregressive models based on a pseudo-likelihood approach
Friday, October 25, 2019
3:30 pm - 4:30 pm
Kshitij Khare, University of Florida
+DS IPLE: Biomedical Data Science and Machine Learning Applications in Healthcare
Sponsor(s):
+DataScience (+DS), Biomedical Engineering (BME), Biostatistics and Bioinformatics, Information Initiative at Duke (iiD), Machine Learning, and Pratt School of Engineering
Wednesday, October 30, 2019
4:30 pm - 6:30 pm
Jessilyn Dunn
Kernel tests of goodness-of-fit using Stein's method
Friday, November 01, 2019
3:30 pm - 4:30 pm
Arthur Gretton - Gatsby Computational Neuroscience Unit - UCL
An Exact Auxiliary Variable Gibbs Sampler for a Class of Diffusions
Friday, November 08, 2019
3:30 pm - 4:30 pm
Vinayak Rao, Purdue
A Bayesian Approach to Mapping Directional Brain Networks
Friday, November 15, 2019
3:30 pm - 4:30 pm
Tingting Zhang, University of Virginia
Shuffled monotone regression
Friday, November 22, 2019
3:30 pm - 4:30 pm
Charles Doss, University of Minnesota
Edge-Selection Priors for Graphical Models and Applications to Complex Biological Data
Friday, December 06, 2019
3:30 pm - 4:30 pm
Marina Vannucci, Rice University
Stochastic nets and Bayesian regularization
Monday, January 06, 2020
3:30 pm - 4:30 pm
Joshua Bon, Queensland University of Technology & ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS)
'Statistics 101' for Network Data Objects
Friday, January 17, 2020
3:30 pm - 4:30 pm
Eric Kolaczyk, Boston University
Latent variable models: from spectral methods to non-convex optimization
Wednesday, January 22, 2020
3:30 pm - 4:30 pm
Kaizheng Wang, Princeton
Handling Sampling and Selection Bias in Association Studies Embedded in Electronic Health Records
Friday, January 24, 2020
3:30 pm - 4:30 pm
Bhramar Mukherjee, University of Michigan
Testing high-dimensional linear hypotheses through spectral shrinkage
Friday, January 31, 2020
3:30 pm - 4:30 pm
Debashis Paul, University of California, Davis
David Page, PhD, Department of Biostatistics and Bioinformatics, Duke University School of Medicine
Friday, February 21, 2020
3:30 pm - 4:30 pm
Siddhartha Chib, Washington University, St. Louis
Friday, February 28, 2020
3:30 pm - 4:30 pm
Siddhartha Chib, Washington University, St. Louis
Long Nguyen, Univeristy of Michigan
Friday, March 06, 2020
3:30 pm - 4:30 pm
Long Nguyen, Univeristy of Michigan
Rebecca Hubbard, Perelman School of Medicine, University of Pennsylvania
Friday, April 24, 2020
3:30 pm - 4:30 pm
Rebecca Hubbard, Perelman School of Medicine, University of Pennsylvania
