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07/19/2023
Beyond Single-Feature Importance with ICECREAM
Which set of features was responsible for a certain output of a machine ...
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05/16/2023
Toward Falsifying Causal Graphs Using a Permutation-Based Test
Understanding the causal relationships among the variables of a system i...
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02/02/2023
Interventional and Counterfactual Inference with Diffusion Models
We consider the problem of answering observational, interventional, and ...
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01/12/2023
Thompson Sampling with Diffusion Generative Prior
In this work, we initiate the idea of using denoising diffusion models t...
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01/10/2023
Manifold Restricted Interventional Shapley Values
Shapley values are model-agnostic methods for explaining model predictio...
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12/14/2022
Sequential Kernelized Independence Testing
Independence testing is a fundamental and classical statistical problem ...
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06/14/2022
DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal models
We introduce DoWhy-GCM, an extension of the DoWhy Python library, that l...
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07/01/2020
Quantifying causal contribution via structure preserving interventions
We introduce 'Causal Information Contribution (CIC)' and 'Causal Varianc...
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12/05/2019
Causal structure based root cause analysis of outliers
We describe a formal approach to identify 'root causes' of outliers obse...
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10/29/2019
Feature relevance quantification in explainable AI: A causality problem
We discuss promising recent contributions on quantifying feature relevan...
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02/19/2018
Analysis of Cause-Effect Inference via Regression Errors
We address the problem of inferring the causal relation between two vari...
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09/03/2017
Estimation of interventional effects of features on prediction
The interpretability of prediction mechanisms with respect to the underl...
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10/11/2016