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06/21/2023
Learning Conditional Instrumental Variable Representation for Causal Effect Estimation
One of the fundamental challenges in causal inference is to estimate the...
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04/24/2023
Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion
An essential problem in causal inference is estimating causal effects fr...
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04/10/2023
Linking a predictive model to causal effect estimation
A predictive model makes outcome predictions based on some given feature...
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02/19/2023
Disentangled Representation for Causal Mediation Analysis
Estimating direct and indirect causal effects from observational data is...
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11/29/2022
Causal Inference with Conditional Instruments using Deep Generative Models
The instrumental variable (IV) approach is a widely used way to estimate...
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08/20/2022
Data-Driven Causal Effect Estimation Based on Graphical Causal Modelling: A Survey
In many fields of scientific research and real-world applications, unbia...
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08/19/2022
Disentangled Representation with Causal Constraints for Counterfactual Fairness
Much research has been devoted to the problem of learning fair represent...
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06/23/2022
Explanatory causal effects for model agnostic explanations
This paper studies the problem of estimating the contributions of featur...
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06/04/2022
Discovering Ancestral Instrumental Variables for Causal Inference from Observational Data
Instrumental variable (IV) is a powerful approach to inferring the causa...
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01/11/2022
Ancestral instrument method for causal inference without a causal graph
Unobserved confounding is the main obstacle to causal effect estimation ...
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11/13/2020
Dependency-based Anomaly Detection: Framework, Methods and Benchmark
Anomaly detection is an important research problem because anomalies oft...
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10/08/2020
Assessing the Fairness of Classifiers with Collider Bias
The increasing maturity of machine learning technologies and their appli...
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09/14/2020
Sufficient Dimension Reduction for Average Causal Effect Estimation
Having a large number of covariates can have a negative impact on the qu...
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07/20/2020
Local search for efficient causal effect estimation
Causal effect estimation from observational data is an important but cha...
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03/25/2020
A general framework for causal classification
In many applications, there is a need to predict the effect of an interv...
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02/24/2020
Towards precise causal effect estimation from data with hidden variables
Causal effect estimation from observational data is a crucial but challe...
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01/28/2020
Causal query in observational data with hidden variables
This paper discusses the problem of causal query in observational data w...
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08/13/2019
Linking Graph Entities with Multiplicity and Provenance
Entity linking is a fundamental database problem with applicationsin dat...
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06/14/2019
Identify treatment effect patterns for personalised decisions
In personalised decision making, evidence is required to determine suita...
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11/06/2018
An exploration of algorithmic discrimination in data and classification
Algorithmic discrimination is an important aspect when data is used for ...
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11/05/2018
FairMod - Making Predictive Models Discrimination Aware
Predictive models such as decision trees and neural networks may produce...
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08/16/2015
From Observational Studies to Causal Rule Mining
Randomised controlled trials (RCTs) are the most effective approach to c...
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08/16/2015