Sep 29, 2022 · We evaluate DIM over 42 adversarial attacks, showing that DIM effectively defenses against all the attacks and outperforms the SOTA on the overall robustness.

Nov 21, 2021 · Inspired by recent advances in brain science, we propose the Denoised Internal Models (DIM), a novel generative autoencoder-based model to tackle this ...

Nov 21, 2021 · We evaluate DIM over 42 adversarial attacks, showing that DIM effectively defenses against all the attacks and outperforms the SOTA on the ...

Denoised Internal Models: A Brain-inspired Autoencoder Against Adversarial Attacks · Abstract. Despite its great success, deep learning severely suffers from ...

Inspired by recent advances in brain science, we propose the denoised internal models (DIM), a novel generative autoencoder-based model to tackle this challenge ...

Inspired by recent advances in brain science, we propose the denoised internal models. (DIM), a novel generative autoencoder-based model to tackle this ...

Jun 11, 2024 · Denoised Internal Models: A Brain-inspired Autoencoder Against Adversarial Attacks. Kaiyuan Liu, Xingyu Li, Yu-Rui Lai, Hang Su, Jiacheng ...

Denoised Internal Models: a Brain-Inspired Autoencoder against Adversarial Attacks · no code implementations • 21 Nov 2021 • Kaiyuan Liu, Xingyu Li, Yurui Lai ...

Oct 18, 2022 · Despite its success, deep neural network (DNN) models are still vulnerable to adversarial attacks. Even with adding human-unrecognizable ...

Denoised Internal Models: A Brain-inspired Autoencoder Against Adversarial Attacks. Machine Intelligence Research. 2022-10 | Journal article. DOI: 10.1007 ...