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Ričards Marcinkevičs

Stochastic Concept Bottleneck Models

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Jun 27, 2024
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Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable?

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Jan 24, 2024
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Signal Is Harder To Learn Than Bias: Debiasing with Focal Loss

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May 31, 2023
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Interpretable and Intervenable Ultrasonography-based Machine Learning Models for Pediatric Appendicitis

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Feb 28, 2023
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Introduction to Machine Learning for Physicians: A Survival Guide for Data Deluge

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Dec 23, 2022
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Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods

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Jul 26, 2022
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A Deep Variational Approach to Clustering Survival Data

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Jun 10, 2021
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Interpretable Models for Granger Causality Using Self-explaining Neural Networks

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Jan 19, 2021
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Interpretability and Explainability: A Machine Learning Zoo Mini-tour

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Dec 03, 2020
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