Are vision transformers always more robust than convolutional neural networks?
Huvudupphovsmän: | Pinto, F, Torr, P, Dokania, PK |
---|---|
Materialtyp: | Conference item |
Språk: | English |
Publicerad: |
NeurIPS
2021
|
Liknande verk
Liknande verk
-
An impartial take to the CNN vs transformer robustness contest
av: Pinto, F, et al.
Publicerad: (2022) -
Adversarial Robustness of Vision Transformers Versus Convolutional Neural Networks
av: Kazim Ali, et al.
Publicerad: (2024-01-01) -
Mix-MaxEnt: improving accuracy and uncertainty estimates of deterministic neural networks
av: Pinto, F, et al.
Publicerad: (2021) -
Mirror Descent view for Neural Network quantization
av: Ajanthan, T, et al.
Publicerad: (2021) -
Using mixup as a regularizer can surprisingly improve accuracy and out-of-distribution robustness
av: Pinto, F, et al.
Publicerad: (2023)