Deep Learning
PromptRestorer: A Prompting Image Restoration Method with Degradation Perception Cong Wang
Image restoration aims to recover clear high-quality images from given degraded ones.
On Measuring Excess Capacity in Neural Networks
We study the excess capacity of deep networks in the context of supervised classification. That is, given a capacity measure of the underlying hypothesis class - in our case, empirical Rademacher complexity - to what extent can we (a priori) constrain this class while retaining an empirical error on a par with the unconstrained regime?
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks
In a seminal paper, Szegedy et al. [Sze+14] observed that deep networks are extremely vulnerable to adversarial examples, namely, very small perturbations to the inputs
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks
In a seminal paper, Szegedy et al. [Sze+14] observed that deep networks are extremely vulnerable to adversarial examples, namely, very small perturbations to the inputs
4cc05b35c2f937c5bd9e7d41d3686fff-Paper.pdf
Our comparisons show that self-attention is not critical for Vision Transformers, as gMLP can achieve the same accuracy.
