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08/23/2023
A Lens to Pandemic Stay at Home Attitudes
We describe the design process and the challenges we met during a rapid ...
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06/15/2023
Mitigating Cold-start Forecasting using Cold Causal Demand Forecasting Model
Forecasting multivariate time series data, which involves predicting fut...
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06/04/2023
Contagion Effect Estimation Using Proximal Embeddings
Contagion effect refers to the causal effect of peers' behavior on the o...
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05/27/2023
Inferring Causal Effects Under Heterogeneous Peer Influence
Causal inference in networks should account for interference, which occu...
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01/16/2023
Data-Driven Estimation of Heterogeneous Treatment Effects
Estimating how a treatment affects different individuals, known as heter...
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08/25/2022
Learning Relational Causal Models with Cycles through Relational Acyclification
In real-world phenomena which involve mutual influence or causal effects...
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06/30/2022
Non-Parametric Inference of Relational Dependence
Independence testing plays a central role in statistical and causal infe...
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06/25/2022
Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure Uncertainty
Estimating how a treatment affects units individually, known as heteroge...
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02/22/2022
Relational Causal Models with Cycles:Representation and Reasoning
Causal reasoning in relational domains is fundamental to studying real-w...
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01/27/2022
Heterogeneous Peer Effects in the Linear Threshold Model
The Linear Threshold Model is a widely used model that describes how inf...
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10/27/2021
Heterogeneous Effects of Software Patches in a Multiplayer Online Battle Arena Game
The popularity of online gaming has grown dramatically, driven in part b...
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06/04/2021
Understanding the Dynamics between Vaping and Cannabis Legalization Using Twitter Opinions
Cannabis legalization has been welcomed by many U.S. states but its role...
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04/15/2020
Minimizing Interference and Selection Bias in Network Experiment Design
Current approaches to A/B testing in networks focus on limiting interfer...
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02/01/2020
Variable-lag Granger Causality and Transfer Entropy for Time Series Analysis
Granger causality is a fundamental technique for causal inference in tim...
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01/29/2020
Correcting for Selection Bias in Learning-to-rank Systems
Click data collected by modern recommendation systems are an important s...
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12/18/2019
Variable-lag Granger Causality for Time Series Analysis
Granger causality is a fundamental technique for causal inference in tim...
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01/31/2019
