226 citations · 266 across the 11 of their papers we have counts for
11 papers
GSLB: The Graph Structure Learning Benchmark
Zhixun Li, Liang Wang, Xin Sun +8
Graph Structure Learning (GSL) has recently garnered considerable attention due to its ability to optimize both the parameters of Graph Neural Networks (GNNs) and the computation g…
Uncovering Neural Scaling Laws in Molecular Representation Learning
Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang +5
Molecular Representation Learning (MRL) has emerged as a powerful tool for drug and materials discovery in a variety of tasks such as virtual screening and inverse design. While th…
TCGF: A unified tensorized consensus graph framework for multi-view representation learning
Xiangzhu Meng, Wei Wei, Qiang Liu +2
Multi-view learning techniques have recently gained significant attention in the machine learning domain for their ability to leverage consistency and complementary information acr…
TiBGL: Template-induced Brain Graph Learning for Functional Neuroimaging Analysis
Xiangzhu Meng, Wei Wei, Qiang Liu +2
In recent years, functional magnetic resonance imaging has emerged as a powerful tool for investigating the human brain's functional connectivity networks. Related studies demonstr…
CvFormer: Cross-view transFormers with Pre-training for fMRI Analysis of Human Brain
Xiangzhu Meng, Qiang Liu, Shu Wu +1
In recent years, functional magnetic resonance imaging (fMRI) has been widely utilized to diagnose neurological disease, by exploiting the region of interest (RoI) nodes as well as…
Deep Stable Multi-Interest Learning for Out-of-distribution Sequential Recommendation
Qiang Liu, Zhaocheng Liu, Zhenxi Zhu +2
Recently, multi-interest models, which extract interests of a user as multiple representation vectors, have shown promising performances for sequential recommendation. However, non…