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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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04/10/2023
Linking a predictive model to causal effect estimation
A predictive model makes outcome predictions based on some given feature...
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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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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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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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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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07/02/2020
Computational methods for cancer driver discovery: A survey
Motivation: Uncovering the genomic causes of cancer, known as cancer dri...
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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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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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08/20/2018
Discovering Context Specific Causal Relationships
With the increasing need of personalised decision making, such as person...
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10/11/2015
ParallelPC: an R package for efficient constraint based causal exploration
Discovering causal relationships from data is the ultimate goal of many ...
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08/28/2015
Mining Combined Causes in Large Data Sets
In recent years, many methods have been developed for detecting causal r...
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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
