Phillip Pope

11 papers A* 5A 1Journal 5
YearRankTypeTitle / Venue / Authors
2023 A* conf
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach.
NeurIPS
Phillip Pope, David Jacobs
2023 J jnl
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach.
CoRR
Phillip Pope, David Jacobs
2022 A* conf
A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes.
CVPR
Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi
2022 J jnl
A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes.
CoRR
Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi
2022 A* conf
Stochastic Training is Not Necessary for Generalization.
ICLR
Jonas Geiping, Micah Goldblum, Phillip Pope, Michael Moeller, Tom Goldstein
2021 A* conf
Influence Functions in Deep Learning Are Fragile.
ICLR
Samyadeep Basu, Phillip Pope, Soheil Feizi
2021 A* conf
The Intrinsic Dimension of Images and Its Impact on Learning.
ICLR
Phillip Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein
2021 J jnl
The Intrinsic Dimension of Images and Its Impact on Learning.
CoRR
Phillip Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein
2020 A conf
Adversarial Robustness of Flow-Based Generative Models.
AISTATS
Phillip Pope, Yogesh Balaji, Soheil Feizi
2020 J jnl
Influence Functions in Deep Learning Are Fragile.
CoRR
Samyadeep Basu, Phillip Pope, Soheil Feizi
2019 J jnl
Adversarial Robustness of Flow-Based Generative Models.
CoRR
Phillip Pope, Yogesh Balaji, Soheil Feizi