most citedNode Embedding from Neural Hamiltonian Orbits in Graph Neural Networks

3 citations · 7 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2023★ 3 cited

Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks

Qiyu Kang, Kai Zhao, Yang Song +2

In the graph node embedding problem, embedding spaces can vary significantly for different data types, leading to the need for different GNN model types. In this paper, we model th…

cs.LG2023★ 1 cited

Graph Neural Convection-Diffusion with Heterophily

Kai Zhao, Qiyu Kang, Yang Song +3

Graph neural networks (GNNs) have shown promising results across various graph learning tasks, but they often assume homophily, which can result in poor performance on heterophilic…

cs.LG2023★ 2 cited

Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks

Feng Ji, See Hian Lee, Hanyang Meng +3

In node classification using graph neural networks (GNNs), a typical model generates logits for different class labels at each node. A softmax layer often outputs a label predictio…

cs.CV2023★ 1 cited

Zoom-VQA: Patches, Frames and Clips Integration for Video Quality Assessment

Kai Zhao, Kun Yuan, Ming Sun +1

Video quality assessment (VQA) aims to simulate the human perception of video quality, which is influenced by factors ranging from low-level color and texture details to high-level…

eess.SP2023

Distributional Signals for Node Classification in Graph Neural Networks

Feng Ji, See Hian Lee, Kai Zhao +2

In graph neural networks (GNNs), both node features and labels are examples of graph signals, a key notion in graph signal processing (GSP). While it is common in GSP to impose sig…

cs.LG2023

Node Embedding from Hamiltonian Information Propagation in Graph Neural Networks

Qiyu Kang, Kai Zhao, Yang Song +3

Graph neural networks (GNNs) have achieved success in various inference tasks on graph-structured data. However, common challenges faced by many GNNs in the literature include the…

cs.CV2022

Learning an Efficient Multimodal Depth Completion Model

Dewang Hou, Yuanyuan Du, Kai Zhao +1

With the wide application of sparse ToF sensors in mobile devices, RGB image-guided sparse depth completion has attracted extensive attention recently, but still faces some problem…