40 citations · 49 across the 6 of their papers we have counts for
3 papers
cs.LG2023★ 4 cited
Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond
Zhiqi Shao, Dai Shi, Andi Han +3
Graph Neural Networks (GNNs) have emerged as one of the leading approaches for machine learning on graph-structured data. Despite their great success, critical computational challe…
cs.LG2023★ 2 cited
Alternating Local Enumeration (TnALE): Solving Tensor Network Structure Search with Fewer Evaluations
Chao Li, Junhua Zeng, Chunmei Li +2
Tensor network (TN) is a powerful framework in machine learning, but selecting a good TN model, known as TN structure search (TN-SS), is a challenging and computationally intensive…
cs.LG2021★ 40 cited
Efficient Tensor Robust PCA under Hybrid Model of Tucker and Tensor Train
Yuning Qiu, Guoxu Zhou, Zhenhao Huang +2
Tensor robust principal component analysis (TRPCA) is a fundamental model in machine learning and computer vision. Recently, tensor train (TT) decomposition has been verified effec…