Publications (7)
On the Hardness of Sampling from Mixture Distributions via Langevin Dynamics
Xiwei Cheng, Kexin Fu, Farzan Farnia
The Langevin Dynamics (LD), which aims to sample from a probability distribution using its score function, has been widely used for analyzing and developing score-based generative…
Non-Convex Joint Community Detection and Group Synchronization via Generalized Power Method
Sijin Chen, Xiwei Cheng, Anthony Man-Cho So
This paper proposes a Generalized Power Method (GPM) to tackle the problem of community detection and group synchronization simultaneously in a direct non-convex manner. Under the…
DrugSAGE:Self-evolving Agent Experience for Efficient State-of-the-Art Drug Discovery
Yikun Zhang, Xiwei Cheng, Tianyu Liu +2
Building state-of-the-art (SOTA) predictive models for drug discovery requires expensive search over tools, architectures, and training strategies. Current LLM-based agents can fin…
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization
Xiangxin Zhou, Xiwei Cheng, Yuwei Yang +3
Recently, 3D generative models have shown promising performances in structure-based drug design by learning to generate ligands given target binding sites. However, only modeling t…
Generalized Group Testing
Xiwei Cheng, Sidharth Jaggi, Qiaoqiao Zhou
In the problem of classical group testing one aims to identify a small subset (of size ) diseased individuals/defective items in a large population (of size ). This process i…
Stability and Generalization in Free Adversarial Training
Xiwei Cheng, Kexin Fu, Farzan Farnia
While adversarial training methods have significantly improved the robustness of deep neural networks against norm-bounded adversarial perturbations, the generalization gap between…
Decomposed Direct Preference Optimization for Structure-Based Drug Design
Xiwei Cheng, Xiangxin Zhou, Yuwei Yang +2
Diffusion models have achieved promising results for Structure-Based Drug Design (SBDD). Nevertheless, high-quality protein subpocket and ligand data are relatively scarce, which h…