3 citations · 5 across the 5 of their papers we have counts for
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cs.LG2023★ 1 cited
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness
Boya Zhang, Weijian Luo, Zhihua Zhang
Adversarial attacks can mislead neural network classifiers. The defense against adversarial attacks is important for AI safety. Adversarial purification is a family of approaches t…
cs.LG2023
Enhancing Adversarial Robustness via Score-Based Optimization
Boya Zhang, Weijian Luo, Zhihua Zhang
Adversarial attacks have the potential to mislead deep neural network classifiers by introducing slight perturbations. Developing algorithms that can mitigate the effects of these…
stat.ML2023
Entropy-based Training Methods for Scalable Neural Implicit Sampler
Weijian Luo, Boya Zhang, Zhihua Zhang
Efficiently sampling from un-normalized target distributions is a fundamental problem in scientific computing and machine learning. Traditional approaches such as Markov Chain Mont…