9 citations · 21 across the 9 of their papers we have counts for
9 papers
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…
Training Energy-Based Models with Diffusion Contrastive Divergences
Weijian Luo, Hao Jiang, Tianyang Hu +3
Energy-Based Models (EBMs) have been widely used for generative modeling. Contrastive Divergence (CD), a prevailing training objective for EBMs, requires sampling from the EBM with…
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…
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…
Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models
Weijian Luo, Tianyang Hu, Shifeng Zhang +3
Due to the ease of training, ability to scale, and high sample quality, diffusion models (DMs) have become the preferred option for generative modeling, with numerous pre-trained m…
A Comprehensive Survey on Knowledge Distillation of Diffusion Models
Weijian Luo
Diffusion Models (DMs), also referred to as score-based diffusion models, utilize neural networks to specify score functions. Unlike most other probabilistic models, DMs directly m…
A Lipschitz Bandits Approach for Continuous Hyperparameter Optimization
Yasong Feng, Weijian Luo, Yimin Huang +1
One of the most critical problems in machine learning is HyperParameter Optimization (HPO), since choice of hyperparameters has a significant impact on final model performance. Alt…
Binary Outcome Copula Regression Model with Sampling Gradient Fitting
Weijian Luo, Mai Wo
Use copula to model dependency of variable extends multivariate gaussian assumption. In this paper we first empirically studied copula regression model with continous response. Bot…
ABM: an automatic supervised feature engineering method for loss based models based on group and fused lasso
Weijian Luo, Yongxian Long
A vital problem in solving classification or regression problem is to apply feature engineering and variable selection on data before fed into models.One of a most popular feature…