VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries

27 October 2021

Papers citing "VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries"

6 / 6 papers shown

Title
Emerging Synergies in Causality and Deep Generative Models: A Survey Guanglin Zhou Shaoan Xie Guang-Yuan Hao Shiming Chen Biwei Huang Xiwei Xu Chen Wang Liming Zhu Lina Yao Kun Zhang AI4CE 53 11 0 29 Jan 2023
On Root Cause Localization and Anomaly Mitigation through Causal Inference Xiao Han Lu Zhang Yongkai Wu Shuhan Yuan 26 7 0 08 Dec 2022
Neural Causal Models for Counterfactual Identification and Estimation K. Xia Yushu Pan Elias Bareinboim CML 39 31 0 30 Sep 2022
Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision Making Miriam Rateike Ayan Majumdar Olga Mineeva Krishna P. Gummadi Isabel Valera OffRL 32 11 0 10 May 2022
Relating Graph Neural Networks to Structural Causal Models Matej Zečević D. Dhami Petar Velickovic Kristian Kersting AI4CE CML 63 53 0 09 Sep 2021
Explaining Visual Models by Causal Attribution Álvaro Parafita Jordi Vitrià CML FAtt 62 35 0 19 Sep 2019