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
arXiv preprint arXiv:1807.02910, 2018
782018
Regularizing black-box models for improved interpretability
G Plumb, M Al-Shedivat, AA Cabrera, A Perer, E Xing, A Talwalkar
arXiv preprint arXiv:1902.06787, 2019
182019
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
Explaining groups of points in low-dimensional representations
G Plumb, J Terhorst, S Sankararaman, A Talwalkar
International Conference on Machine Learning, 7762-7771, 2020
42020
A Learning Theoretic Perspective on Local Explainability
J Li, V Nagarajan, G Plumb, A Talwalkar
arXiv preprint arXiv:2011.01205, 2020
12020
Finding and Fixing Spurious Patterns with Explanations
G Plumb, MT Ribeiro, A Talwalkar
arXiv preprint arXiv:2106.02112, 2021
2021
Sanity Simulations for Saliency Methods
JS Kim, G Plumb, A Talwalkar
arXiv preprint arXiv:2105.06506, 2021
2021
Towards Connecting Use Cases and Methods in Interpretable Machine Learning
V Chen, J Li, JS Kim, G Plumb, A Talwalkar
arXiv preprint arXiv:2103.06254, 2021
2021
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-Assisted …, 2017
2017
The system can't perform the operation now. Try again later.
Articles 1–9