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Gregory Plumb
Gregory Plumb
Verified email at andrew.cmu.edu
Title
Cited by
Cited by
Year
Model agnostic supervised local explanations
G Plumb, D Molitor, A Talwalkar
NeurIPS 2018, 2018
1202018
Regularizing black-box models for improved interpretability
G Plumb, M Al-Shedivat, AA Cabrera, A Perer, E Xing, A Talwalkar
NeurIPS 2020, 2020
34*2020
Interpretable machine learning: Moving from mythos to diagnostics
V Chen, J Li, JS Kim, G Plumb, A Talwalkar
Queue 19 (6), 28-56, 2022
14*2022
Explaining groups of points in low-dimensional representations
G Plumb, J Terhorst, S Sankararaman, A Talwalkar
ICML 2020, 2020
102020
SnFFT: a Julia toolkit for Fourier analysis of functions over permutations
G Plumb, D Pachauri, R Kondor, V Singh
The Journal of Machine Learning Research 16 (1), 3469-3473, 2015
7*2015
A Learning Theoretic Perspective on Local Explainability
J Li, V Nagarajan, G Plumb, A Talwalkar
ICLR 2021, 2021
62021
Finding and fixing spurious patterns with explanations
G Plumb, MT Ribeiro, A Talwalkar
arXiv preprint arXiv:2106.02112, 2021
42021
Sanity simulations for saliency methods
JS Kim, G Plumb, A Talwalkar
arXiv preprint arXiv:2105.06506, 2021
42021
Simulated User Studies for Explanation Evaluation
V Chen, G Plumb, N Topin, A Talwalkar
eXplainable AI approaches for debugging and diagnosis., 2021
12021
Evaluating Systemic Error Detection Methods using Synthetic Images
G Plumb, N Johnson, ┴ Cabrera, MT Ribeiro, A Talwalkar
ICML 2022: Workshop on Spurious Correlations, Invariance and Stability, 2022
2022
Use-Case-Grounded Simulations for Explanation Evaluation
V Chen, N Johnson, N Topin, G Plumb, A Talwalkar
arXiv preprint arXiv:2206.02256, 2022
2022
Modeling Cognitive Trends in Preclinical Alzheimer’s Disease (AD) via Distributions over Permutations
G Plumb, L Clark, SC Johnson, V Singh
International Conference on Medical Image Computing and Computer-Assistedá…, 2017
2017
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Articles 1–12