11 citations · 22 across the 17 of their papers we have counts for
4 papers · 1 filter
PEGNet: A Physics-Embedded Graph Network for Long-Term Stable Multiphysics Simulation
Can Yang, Zhenzhong Wang, Junyuan Liu +2
Accurate and efficient simulations of physical phenomena governed by partial differential equations (PDEs) are important for scientific and engineering progress. While traditional…
Adversarial Learning for Neural PDE Solvers with Sparse Data
Yunpeng Gong, Yongjie Hou, Zhenzhong Wang +2
Neural network solvers for partial differential equations (PDEs) have made significant progress, yet they continue to face challenges related to data scarcity and model robustness.…
Explainable Molecular Property Prediction: Aligning Chemical Concepts with Predictions via Language Models
Zhenzhong Wang, Zehui Lin, Wanyu Lin +3
Providing explainable molecular property predictions is critical for many scientific domains, such as drug discovery and material science. Though transformer-based language models…
Multi-View Subgraph Neural Networks: Self-Supervised Learning with Scarce Labeled Data
Zhenzhong Wang, Qingyuan Zeng, Wanyu Lin +2
While graph neural networks (GNNs) have become the de-facto standard for graph-based node classification, they impose a strong assumption on the availability of sufficient labeled…