BayesIMP: Uncertainty Quantification for Causal Data Fusion

BayesIMP: Uncertainty Quantification for Causal Data Fusion

7 June 2021

Jean-François Ton

Javier I. González

Dino Sejdinovic

Papers citing "BayesIMP: Uncertainty Quantification for Causal Data Fusion"

18 / 18 papers shown

Title
Kernel Quantile Embeddings and Associated Probability Metrics Masha Naslidnyk Siu Lun Chau F. Briol Krikamol Muandet 70 0 0 26 May 2025
Computing Exact Shapley Values in Polynomial Time for Product-Kernel Methods Majid Mohammadi Siu Lun Chau Krikamol Muandet FAtt 170 0 0 22 May 2025
Integral Imprecise Probability Metrics Siu Lun Chau Michele Caprio Krikamol Muandet 86 0 0 22 May 2025
Kernel-based estimators for functional causal effects Yordan P. Raykov Hengrui Luo Justin Strait Wasiur R. KhudaBukhsh CML 196 0 0 06 Mar 2025
Deconditional Downscaling with Gaussian Processes Siu Lun Chau S. Bouabid Dino Sejdinovic BDL 59 22 0 27 May 2021
Multi-task Causal Learning with Gaussian Processes Virginia Aglietti Theodoros Damoulas Mauricio A. Alvarez Javier I. González CML 47 18 0 27 Sep 2020
Causal Bayesian Optimization Virginia Aglietti Xiaoyu Lu Andrei Paleyes Javier Gonz' alez CML 30 49 0 24 May 2020
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 222 1,410 0 21 Oct 2019
Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings Jean-François Ton Lucian Chan Yee Whye Teh Dino Sejdinovic 43 13 0 05 Jun 2019
Kernel Instrumental Variable Regression Rahul Singh M. Sahani Arthur Gretton 87 174 0 01 Jun 2019
Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds Kelvin Hsu Richard Nock F. Ramos BDL 25 5 0 01 Sep 2018
Counterfactual Mean Embeddings Krikamol Muandet Motonobu Kanagawa Sorawit Saengkyongam S. Marukatat CML OffRL 82 40 0 22 May 2018
Causal Inference via Kernel Deviance Measures Jovana Mitrović Dino Sejdinovic Yee Whye Teh CML 43 62 0 12 Apr 2018
Bayesian Approaches to Distribution Regression H. Law Danica J. Sutherland Dino Sejdinovic Seth Flaxman OOD UQCV BDL 70 37 0 11 May 2017
Large-Scale Kernel Methods for Independence Testing Qinyi Zhang Sarah Filippi Arthur Gretton Dino Sejdinovic 103 132 0 25 Jun 2016
Uncertain programming model for multi-item solid transportation problem Hasan Dalman 104 64 0 31 May 2016
Bayesian Learning of Kernel Embeddings Seth Flaxman Dino Sejdinovic John P. Cunningham Sarah Filippi BDL 52 44 0 07 Mar 2016
Kernel Bayes' rule Kenji Fukumizu Le Song Arthur Gretton 80 60 0 29 Sep 2010