Do We Really Need Graph Convolution During Training? Light Post-Training Graph-ODE for Efficient Recommendationby Weizhi…
Masked Graph Learning with Recurrent Alignment for Multimodal Emotion Recognition in Conversationby Tao Meng, Fuchen…
The Solution for The PST-KDD-2024 OAG-Challengeby Shupeng Zhong, Xinger Li, Shushan Jin, Yang YangFirst submitted…
HyperAggregation: Aggregating over Graph Edges with Hypernetworksby Nicolas Lell, Ansgar ScherpFirst submitted to arxiv on:…
Accounting for Work Zone Disruptions in Traffic Flow Forecastingby Yuanjie Lu, Amarda Shehu, David LattanziFirst…
Causality-driven Sequence Segmentation for Enhancing Multiphase Industrial Process Data Analysis and Soft Sensingby Yimeng He,…
Rethinking Data Input for Point Cloud Upsamplingby Tongxu ZhangFirst submitted to arxiv on: 5 Jul…
Graph Neural Network as Computationally Efficient Emulator of Ice-sheet and Sea-level System Model (ISSM)by Younghyun…
Bridging Smoothness and Approximation: Theoretical Insights into Over-Smoothing in Graph Neural Networksby Guangrui Yang, Jianfei…
YZS-model: A Predictive Model for Organic Drug Solubility Based on Graph Convolutional Networks and Transformer-Attentionby…