activity
20222024
most citedGraph Neural Processes for Spatio-Temporal Extrapolation

25 citations · 72 across the 19 of their papers we have counts for

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10 papers · 1 filter

cs.LG2024

Decision-focused Graph Neural Networks for Combinatorial Optimization

Yang Liu, Chuan Zhou, Peng Zhang +3

In recent years, there has been notable interest in investigating combinatorial optimization (CO) problems by neural-based framework. An emerging strategy to tackle these challengi…

cs.LG20243 cited

Combinatorial Optimization with Automated Graph Neural Networks

Yang Liu, Peng Zhang, Yang Gao +3

In recent years, graph neural networks (GNNs) have become increasingly popular for solving NP-hard combinatorial optimization (CO) problems, such as maximum cut and maximum indepen…

cs.LG202415 cited

Collaborate to Adapt: Source-Free Graph Domain Adaptation via Bi-directional Adaptation

Zhen Zhang, Meihan Liu, Anhui Wang +4

Unsupervised Graph Domain Adaptation (UGDA) has emerged as a practical solution to transfer knowledge from a label-rich source graph to a completely unlabelled target graph. Howeve…

cs.LG202412 cited

Geometric-Facilitated Denoising Diffusion Model for 3D Molecule Generation

Can Xu, Haosen Wang, Weigang Wang +2

Denoising diffusion models have shown great potential in multiple research areas. Existing diffusion-based generative methods on de novo 3D molecule generation face two major chall…

cs.LG2023

Debunking Free Fusion Myth: Online Multi-view Anomaly Detection with Disentangled Product-of-Experts Modeling

Hao Wang, Zhi-Qi Cheng, Jingdong Sun +4

Multi-view or even multi-modal data is appealing yet challenging for real-world applications. Detecting anomalies in multi-view data is a prominent recent research topic. However,…

cs.LG2023

Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors

Han Liu, Xingshuo Huang, Xiaotong Zhang +6

Decision-based methods have shown to be effective in black-box adversarial attacks, as they can obtain satisfactory performance and only require to access the final model predictio…