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The Program Hypergraph: Multi-Way Relational Structure for Geometric Algebra, Sp...
Higher-order Neural Additive Models: An Interpretable Machine Learning Model wit...
Tackling Over-smoothing on Hypergraphs: A Ricci Flow-guided Neural Diffusion App...
The Intelligible and Effective Graph Neural Additive
Totally Dynamic Hypergraph Neural Network
Groups, graphs, and hypergraphs: average sizes of kernels of generic matrices wi...
Conic Formulations of Transport Metrics for Unbalanced Measure Networks and Hype...
Hypergraph Co-Optimal Transport: Metric and Categorical Properties
The Topological Structures of the Orders of Hypergraphs
Stability of Hypergraph Invariants and Transformations
超图对于建模复杂系统中普遍存在的高阶交互至关重要,因而需要专门的神经网络架构。超图神经网络(HGNNs)虽已广泛流行,但仍面临关键性局限。基于张量的超图神经网络...
Graphs are maximally expressive for higher-order interactions
Hypergraphs and simplicial complexes in focus: a roadmap for
https://link.springer.com/book/10.1007/978-981-99-0185-2
Evolving Dependencies: From Graphs to Hypergraphs and
Elicitation-Augmented Bayesian Optimization
Online Sharp-Calibrated Bayesian Optimization
Susceptibilities and Patterning: A Primer on Linear Response in
在网络环境中,有效的动态干预分配不仅需决定对谁干预(whom),还需决定何时干预(when),以通过网络溢出效应放大政策影响。早期对高连接度节点的干预可能触发传...
MTRBO: Multiple trust-region based Bayesian optimization
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