Variational Causal

Variational causal inference aims to estimate causal effects from observational data, particularly in scenarios with high-dimensional outcomes and limited covariates, by leveraging both individual-level information and the responses of similar subjects. Current research focuses on developing robust model architectures, including variational autoencoders and graph neural networks, to handle challenges like domain shift, missing data, and the identification of latent causal structures. These methods are improving the accuracy and generalizability of causal effect estimation across diverse applications, such as personalized medicine, reinforcement learning, and the synthesis of causally-informed datasets.

Papers

October 16, 2024

Counterfactual Generative Modeling with Variational Causal Inference
Yulun Wu, Louie McConnell, Claudia Iriondo
Variational Inference Counterfactual Task Counterfactual Generative Variational Causal

March 12, 2024

Probabilistic Easy Variational Causal Effect
Usef Faghihi, Amir Saki
Causal Inference Causal Effect Random Vector Variational Causal

June 23, 2023

Variational Counterfactual Prediction under Runtime Domain Corruption
Hechuan Wen, Tong Chen, Li Kheng Chai, Shazia Sadiq, Junbin Gao, Hongzhi Yin
Domain Shift Causal Effect Estimation Runtime Analysis Counterfactual Prediction Variational Causal Runtime Error

October 20, 2022

Causal Structural Hypothesis Testing and Data Generation Models
Jeffrey Jiang, Omead Pooladzandi, Sunay Bhat, Gregory Pottie
Structural Prior Causal System Variational Causal Data Generation Model

September 30, 2022

Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information
Yulun Wu, Robert A. Barton, Zichen Wang, Vassilis N. Ioannidis, Carlo De Donno, Layne C. Price, Luis F. Voloch, George Karypis
Relational Information Regulatory Network Variational Causal Counterfactual Perturbation

September 13, 2022

Variational Causal Inference
Yulun Wu, Layne C. Price, Zichen Wang, Vassilis N. Ioannidis, Robert A. Barton, George Karypis
High Dimension Variational Causal Counterfactual Treatment

August 30, 2022

Identifying Weight-Variant Latent Causal Models
Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
Latent Causal Causal Representation Variational Causal Latent Causal Representation

August 12, 2022

Probabilistic Variational Causal Approach in Observational Studies
Usef Faghihi, Amir Saki
Causal Effect Causal Relation Causal Analysis Causal Reasoning Novel Causal Model Variational Causal

July 19, 2022

Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning
Wenhao Ding, Haohong Lin, Bo Li, Ding Zhao
Reinforcement Learning Causal Discovery Causal Graph Goal Conditioned Reinforcement Learning Causal Reinforcement Learning Variational Causal

June 22, 2022

Variational Causal Dynamics: Discovering Modular World Models from Interventions
Anson Lei, Bernhard Schölkopf, Ingmar Posner
Variational Inference Causal Discovery World Model Health Intervention Causal Graphical Model Variational Causal Latent World Model