33 citations · 84 across the 11 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.LG2023★ 6 cited
Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation
Jialin Chen, Yuelin Wang, Cristian Bodnar +3
Graph convolutions have been a pivotal element in learning graph representations. However, recursively aggregating neighboring information with graph convolutions leads to indistin…
cs.LG2023★ 1 cited
An Effective Universal Polynomial Basis for Spectral Graph Neural Networks
Keke Huang, Pietro Liò
Spectral Graph Neural Networks (GNNs), also referred to as graph filters have gained increasing prevalence for heterophily graphs. Optimal graph filters rely on Laplacian eigendeco…
q-bio.QM2023★ 20 cited
Graph Denoising Diffusion for Inverse Protein Folding
Kai Yi, Bingxin Zhou, Yiqing Shen +2
Inverse protein folding is challenging due to its inherent one-to-many mapping characteristic, where numerous possible amino acid sequences can fold into a single, identical protei…