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Where Does My Model Underperform? A Human Evaluation of Slice Discovery Algorithms.
Nari Johnson, Alexander Cabrera, Gregory Plumb, Ameet Talwalkar.
HCOMP, 2023.
[paper]
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Towards a More Rigorous Science of Blindspot Discovery in Image Classification Models
Gregory Plumb*, Nari Johnson*, Alexander Cabrera, Ameet Talwalkar.
TMLR, 2023.
[paper]
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Use-Case-Grounded Simulations for Explanation Evaluation
Valerie Chen, Nari Johnson, Nicholay Topin, Gregory Plumb, Ameet Talwalkar.
NeurIPS 2022.
[paper]
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Finding and Fixing Spurious Patterns with Explanations.
Gregory Plumb, Marco Tulio Ribeiro, Ameet Talwalkar.
TMLR 2022.
[paper]
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Sanity Simulations for Saliency Methods.
Joon Sik Kim, Gregory Plumb, Ameet Talwalkar.
ICML 2022.
[paper]
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Interpretable Machine Learning: Moving from mythos to diagnostics
Valerie Chen, Jeffrey Li, Joon Sik Kim, Gregory Plumb, Ameet Talwalkar.
ACM Queue 2022.
[paper]
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A Learning Theoretic Perspective on Local Explainability.
Jeffrey Li, Vaishnavh Nagarajan, Gregory Plumb, Ameet Talwalkar.
ICLR 2021.
[paper]
[blog]
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Regularizing Black-box Models for Improved Interpretability.
Gregory Plumb, Maruan Al-Shedivat, Angel Alexander Cabrera, Adam Perer, Eric Xing, Ameet Talwalkar.
NeurIPS 2020.
[paper]
[code]
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Explaining Groups of Points in Low-Dimensional Representations.
Gregory Plumb, Jonathan Terhorst, Sriram Sankararaman, Ameet Talwalkar.
ICML 2020.
[paper]
[code]
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Model Agnostic Supervised Local Explanations.
Gregory Plumb, Denali Molitor, Ameet Talwalkar.
NeurIPS 2018.
[paper]
[code]
[blog]
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Modeling Cognitive Trends in Preclinical Alzheimer's Disease (AD) via Distributions over Permutations.
Gregory Plumb, Lindsay Clark, Sterling C. Johnson, Vikas Singh.
MICCAI 2017.
[paper]
[code]
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SnFFT: A Julia Toolkit for Fourier Analysis of Functions over Permutations.
Gregory Plumb, Deepti Pachauri, Risi Kondor, Vikas Singh.
JMLR 2015.
[paper]
[code]
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