Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
preprints
High-dimensional functional graphical model structure learning via neighborhood selection approach
Submitted, 2021+
Zhao, B., Zhai, P. S., Wang, Y. S., Kolar, M.
Confidence Sets for Causal Orderings
Submitted, 2023+
Wang, Y. S., Kolar, M., Drton, M. (Recieved the Tom Ten Have Award at the 2023 American Causal Inference Conference)
publications
Empirical likelihood for linear structural equation models with dependent errors
Stat, 2017
Wang, Y. S., Drton, M.
A variational EM method for mixed membership models with multivariate rank data: An analysis of public policy preferences
Annals of Applied Statistics, 2017
Wang, Y. S., Matsueda R., Erosheva, E. A.
On the use of bootstrap with variational inference: Theory, interpretation, and a two-sample test example
Annals of Applied Statistics, 2018
Chen, Y. C., Wang, Y. S., Erosheva, E. A.
Computation of maximum likelihood estimates in cyclic structural equation models
Annals of Statistics, 2019
Drton, M., Fox, C., Wang, Y. S.
Direct estimation of differential functional graphical models
NeurIPS, 2019
Zhao, B., Wang, Y. S., Kolar, M.
On causal discovery with an equal-variance assumption
Biometrika, 2019
Chen, W., Drton, M., Wang, Y. S.
High-dimensional causal discovery under non-Gaussianity
Biometrika, 2020
Wang, Y. S., Drton, M.
Robust Inference for High-Dimensional Linear Models via Residual Randomization
ICML, 2021
Wang, Y. S., Lee, S.K., Toulis, P., Kolar, M. (Note: An error in the statement of Theorem 2 in the ICML version has been fixed in the Arxiv Version)
FuDGE: Functional Differential Graph Estimation with fully and discretely observed curves
Journal of Machine Learning Research, 2022
Zhao, B., Wang, Y. S., Kolar, M.
Gender-based homophily in collaborations across a heterogeneous scholarly landscape
Plos One, 2023
Wang, Y. S., Lee, C. J., West, J. D., Bergstrom, C. T., Erosheva, E. A.
Causal discovery with unobserved confounding and non- Gaussian data
Journal of Machine Learning Research, 2023
Wang, Y. S., Drton, M.
teaching
STAT 311: Elements of Statistical Methods
Undergraduate course, Univ of Washington, STAT 311, 2016
Grad School 101
Graduate level, Cornell, 2021