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06/12/2023
On the Robustness of Removal-Based Feature Attributions
To explain complex models based on their inputs, many feature attributio...
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06/05/2023
Estimating Conditional Mutual Information for Dynamic Feature Selection
Dynamic feature selection, where we sequentially query features to make ...
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01/02/2023
Learning to Maximize Mutual Information for Dynamic Feature Selection
Feature selection helps reduce data acquisition costs in ML, but the sta...
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06/10/2022
Learning to Estimate Shapley Values with Vision Transformers
Transformers have become a default architecture in computer vision, but ...
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07/15/2021
FastSHAP: Real-Time Shapley Value Estimation
Shapley values are widely used to explain black-box models, but they are...
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06/12/2021
Disrupting Model Training with Adversarial Shortcuts
When data is publicly released for human consumption, it is unclear how ...
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12/02/2020
Improving KernelSHAP: Practical Shapley Value Estimation via Linear Regression
The Shapley value solution concept from cooperative game theory has beco...
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11/21/2020
Explaining by Removing: A Unified Framework for Model Explanation
Researchers have proposed a wide variety of model explanation approaches...
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11/06/2020
Feature Removal Is a Unifying Principle for Model Explanation Methods
Researchers have proposed a wide variety of model explanation approaches...
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04/01/2020
Understanding Global Feature Contributions Through Additive Importance Measures
Understanding the inner workings of complex machine learning models is a...
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05/03/2019
Temporal Graph Convolutional Networks for Automatic Seizure Detection
Seizure detection from EEGs is a challenging and time consuming clinical...
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02/16/2018