CONGRATULATIONS to Kun Yue for receiving a best student paper award in the WNAR student paper competition for her recent work on estimating variance components in large linear mixed models.
The newest version of netgsa package offers considerable speedups and interactive network visualization. Check out the accompanying paper published in PLoS Comp Bio for details and the vignette for examples.
Our paper, Neural Granger Causality, which develops a flexible framework for estimating Granger causality using sparse deep neural networks, has been published at IEEE-TPAMI.
CONGRATULATIONS to our graduating class of 2021, Aaron Hudson and Xu (Steven) Wang. Having successfully passed their final exams, Aaron and Steven will soon start the next chapter of their journey: Aaron as a postdoc at UC-Berkeley and Steven as a data scientist at Facebook. Well done guys!
In our recent paper, Emily Fox and I review the classical notion of Granger causality as well as recent developments based on statistical machine learning.
CONGRATULATIONS to Aaron Hudson for winning the 2021 David P. Byar Early Career Award. You can read more about Aaron's great work and award here and find the award winning paper on arxiv.
I am excited to start working on my new R01 grant focused on developing novel statistical inference procedures for biomedical big data.
Welcome to new postdoctoral fellows, Shubhadeep Chakraborty from Texas A&M University and Lu Xia from University of Michigan. Great to have you both join the lab!
In collaboration with Simge Küçükyavuz, I have recently revisited my optimization roots to develop mixed integer programming algorithms for learning directed acyclic graphs (DAGs) from observational data. Our first paper has been accepted in INFORMS Journal on Optimization and is available here. Our second paper, available on arXiv, develops a second order conic program for DAG learning with a data-driven early stopping criterion that guarantees a consistent estimate.
Now former postdoc at the lab, Yue Wang has joined Arizona State University as an Assistant Professor of Statistics. CONGRATULATIONS, Yue!
In collaboration with the Promislow Lab, we recently investigated changes in metabolic networks associated with the effect of dietary restrictions on longevity. The resulting paper, highlighted with a perspective article in PLoS Genetics, uses our recent tool for differential network analysis, available in the CorDiffViz package.
We have two new papers in JMLR on estimation of undirected and directed graphical models:
- The Reduced PC-Algorithm: Improved Causal Structure Learning in Large Random Networks (link)
- Generalized Score Matching for Non-Negative Data (link)