research
∙
02/06/2023
Causal Shift-Response Functions with Neural Networks: The Health Benefits of Lowering Air Quality Standards in the US
Policymakers are required to evaluate the health benefits of reducing th...
share
research
∙
10/21/2022
Targeted active learning for probabilistic models
A fundamental task in science is to design experiments that yield valuab...
research
∙
09/25/2022
Weather2vec: Representation Learning for Causal Inference with Non-Local Confounding in Air Pollution and Climate Studies
Estimating the causal effects of a spatially-varying intervention on a s...
research
∙
05/09/2022
A Comparative Tutorial of Bayesian Sequential Design and Reinforcement Learning
Reinforcement Learning (RL) is a computational approach to reward-driven...
research
∙
03/22/2022
Bayesian Nonparametric Adjustment of Confounding
Analysis of observational studies increasingly confronts the challenge o...
research
∙
02/28/2022
Estimating Importation Risk of Covid-19 in Hurricane Evacuations: A Prediction Framework Applied to Hurricane Laura in Texas
In August 2020, as Texas was coming down from a large summer COVID-19 su...
research
∙
05/27/2021
Adversarial Intrinsic Motivation for Reinforcement Learning
Learning with an objective to minimize the mismatch with a reference dis...
research
∙
11/19/2019
Large-Scale Spatiotemporal Density Smoothing with the Graph-fused Elastic Net: Application to Ride-sourcing Driver Productivity Analysis
Ride-sourcing or transportation network companies (TNCs) provide on-dema...
research
∙
10/15/2018
Random clique covers for graphs with local density and global sparsity
Large real-world graphs tend to be sparse, but they often contain densel...
research
∙
09/27/2018
