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08/30/2023
Causal Strategic Learning with Competitive Selection
We study the problem of agent selection in causal strategic learning und...
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05/24/2023
Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models
We present a novel approach for explaining Gaussian processes (GPs) that...
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05/26/2022
Explaining Preferences with Shapley Values
While preference modelling is becoming one of the pillars of machine lea...
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02/02/2022
Giga-scale Kernel Matrix Vector Multiplication on GPU
Kernel matrix-vector multiplication (KMVM) is a foundational operation i...
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10/18/2021
RKHS-SHAP: Shapley Values for Kernel Methods
Feature attribution for kernel methods is often heuristic and not indivi...
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06/07/2021
BayesIMP: Uncertainty Quantification for Causal Data Fusion
While causal models are becoming one of the mainstays of machine learnin...
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05/27/2021
Deconditional Downscaling with Gaussian Processes
Refining low-resolution (LR) spatial fields with high-resolution (HR) in...
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08/23/2020
Kernel-based Graph Learning from Smooth Signals: A Functional Viewpoint
The problem of graph learning concerns the construction of an explicit t...
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06/06/2020
Learning Inconsistent Preferences with Kernel Methods
We propose a probabilistic kernel approach for preferential learning fro...
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05/08/2020