Brian Barr

Orcid: 0000-0002-4424-3448

According to our database1, Brian Barr authored at least 16 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Visual Exploration of Machine Learning Model Behavior With Hierarchical Surrogate Rule Sets.
IEEE Trans. Vis. Comput. Graph., February, 2024

Gaussian Process Neural Additive Models.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Calibrate: Interactive Analysis of Probabilistic Model Output.
IEEE Trans. Vis. Comput. Graph., 2023

The Disagreement Problem in Faithfulness Metrics.
CoRR, 2023

2022
BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence.
CoRR, 2022

Topological Representations of Local Explanations.
CoRR, 2022

SUBPLEX: A Visual Analytics Approach to Understand Local Model Explanations at the Subpopulation Level.
IEEE Computer Graphics and Applications, 2022

GALE: Globally Assessing Local Explanations.
Proceedings of the Topological, 2022

Understanding Counterfactual Generation using Maximum Mean Discrepancy.
Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

An Interpretable Deep Classifier for Counterfactual Generation.
Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

2021
Counterfactual Explanations via Latent Space Projection and Interpolation.
CoRR, 2021

Science-Guided Machine Learning for Wall-Modeled Large Eddy Simulation.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Latent-CF: A Simple Baseline for Reverse Counterfactual Explanations.
CoRR, 2020

Melody: Generating and Visualizing Machine Learning Model Summary to Understand Data and Classifiers Together.
CoRR, 2020

SUBPLEX: Towards a Better Understanding of Black Box Model Explanations at the Subpopulation Level.
CoRR, 2020

Towards Ground Truth Explainability on Tabular Data.
CoRR, 2020


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