Phillip E. Pope
Phillip E. Pope
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Explainability methods for graph convolutional neural networks
PE Pope, S Kolouri, M Rostami, CE Martin, H Hoffmann
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
Sliced Wasserstein auto-encoders
S Kolouri, PE Pope, CE Martin, GK Rohde
International Conference on Learning Representations, 2018
Sliced-wasserstein autoencoder: An embarrassingly simple generative model
S Kolouri, PE Pope, CE Martin, GK Rohde
arXiv preprint arXiv:1804.01947, 2018
Influence functions in deep learning are fragile
S Basu, P Pope, S Feizi
arXiv preprint arXiv:2006.14651, 2020
Adversarial robustness of flow-based generative models
P Pope, Y Balaji, S Feizi
International Conference on Artificial Intelligence and Statistics, 3795-3805, 2020
Learning a domain-invariant embedding for unsupervised domain adaptation using class-conditioned distribution alignment
AJ Gabourie, M Rostami, PE Pope, S Kolouri, K Kim
2019 57th Annual Allerton Conference on Communication, Control, and …, 2019
Discovering molecular functional groups using graph convolutional neural networks
P Pope, S Kolouri, M Rostrami, C Martin, H Hoffmann
arXiv preprint arXiv:1812.00265, 2018
The Intrinsic Dimension of Images and Its Impact on Learning
P Pope, C Zhu, A Abdelkader, M Goldblum, T Goldstein
arXiv preprint arXiv:2104.08894, 2021
Stochastic training is not necessary for generalization
J Geiping, M Goldblum, PE Pope, M Moeller, T Goldstein
arXiv preprint arXiv:2109.14119, 2021
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