DO ADVERSARIALLY ROBUST IMAGENET MODELS TRANSFER BETTER?

von Salman, Hadi
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 5 of 27 (2021)

Datamodels: Understanding Predictions with Data and Data with Predictions

von Ilyas, Andrew
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 12 of 33 (2023)

ADVERSARIAL EXAMPLES ARE NOT BUGS, THEY ARE FEATURES

von Ilyas, Andrew
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 1 of 20 (2020)

IDENTIFYING STATISTICAL BIAS IN DATASET REPLICATION

von Engstrom, Logan
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 4 of 15 (2021)

Unadversarial Examples: Designing Objects for Robust Vision

von Salman, Hadi
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 19 of 36 (2022)

IMAGE SYNTHESIS WITH A SINGLE (ROBUST) CLASSIFIER

von Santurkar, Shibani
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 2 of 20 (2020)

3DB: A Framework for Debugging Computer Vision Models

von Leclerc, Guillaume
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 12 of 50 (2023)