Search Results for author:
Found 6 papers, 3 papers with code
Sequential Convolution and Runge-Kutta Residual Architecture for Image Compressed Sensing
In recent years, Deep Neural Networks (DNN) have empowered Compressed Sensing (CS) substantially and have achieved high reconstruction quality and speed far exceeding traditional CS methods.
Ranked #1 on
Image Compression
on BSDS500
SpecFormer: Guarding Vision Transformer Robustness via Maximum Singular Value Penalization
In this study, we address this gap by introducing SpecFormer, specifically designed to enhance ViTs' resilience against adversarial attacks, with support from carefully derived theoretical guarantees.
On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective
In this paper, we conduct a thorough evaluation of the robustness of ChatGPT from the adversarial and out-of-distribution (OOD) perspective.
Bayesian Optimization Augmented with Actively Elicited Expert Knowledge
We design a multi-task learning architecture for this task, with the goal of jointly eliciting the expert knowledge and minimizing the objective function.
Data-free Backdoor Removal based on Channel Lipschitzness
Pruning these channels was then shown to be effective in mitigating the backdoor behaviors.
Learning Class Unique Features in Fine-Grained Visual Classification
A major challenge in Fine-Grained Visual Classification (FGVC) is distinguishing various categories with high inter-class similarity by learning the feature that differentiate the details.
Ranked #12 on
Fine-Grained Image Classification
on FGVC Aircraft
