7 citations · 7 across the 6 of their papers we have counts for
5 papers · 1 filter
Weisfeiler Lehman Test on Combinatorial Complexes: Generalized Expressive Power of Topological Neural Networks
Jiawen Chen, Qi Shao, Zhiqiang Ge +2
Topological neural networks have emerged as effective tools for modeling higher-order relational structures beyond pairwise graphs, including hypergraphs, simplicial complexes, and…
From Uniform to Learned Graph Priors: Diffusion for Structure Discovery
Qi Shao, Hao Guo, Jiawen Chen +2
Neural relational inference (NRI) methods discover interaction graphs from trajectories through variational reasoning on discrete potential edges. However, these methods typically…
Predicting Dynamics of Ultra-Large Complex Systems by Inferring Governing Equations
Qi Shao, Duxin Chen, Jiawen Chen +5
Predicting the behavior of ultra-large complex systems, from climate to biological and technological networks, is a central unsolved challenge. Existing approaches face a fundament…
CCMamba: Topologically-Informed Selective State-Space Networks on Combinatorial Complexes for Higher-Order Graph Learning
Jiawen Chen, Qi Shao, Mingtong Zhou +2
Topological deep learning has emerged as a powerful paradigm for modeling higher-order relational structures beyond pairwise interactions that standard graph neural networks fail t…
Decoupling Spatio-Temporal Prediction: When Lightweight Large Models Meet Adaptive Hypergraphs
Jiawen Chen, Qi Shao, Duxin Chen +1
Spatio-temporal prediction is a pivotal task with broad applications in traffic management, climate monitoring, energy scheduling, etc. However, existing methodologies often strugg…