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Graph Theory-Based Sneak Circuit Analysis and Trigger of Semi-DAB With Parasitic Parameters

IEEE transactions on power electronics, 2023
Parasitic parameters and dynamic sneak paths would lead to unexpected phenomena, exerting negative impacts on the reliability and safety of semi-dual active bridge (S-DAB) dc–dc converter.
Yiting Xiao   +4 more
semanticscholar   +1 more source

Graph-Theory-Based Derivation, Modeling, and Control of Power Converter Systems

IEEE Journal of Emerging and Selected Topics in Power Electronics, 2022
Graph-theoretical approaches have been widely applied in many disciplines, however, their implementation in power electronics converters and systems is still in the exploring stage.
Yuzhuo Li   +3 more
semanticscholar   +1 more source

Bridging and Compressing Feature and Semantic Spaces for Robust Graph Neural Networks: An Information Theory Perspective

open access: closedProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Luying Zhong   +4 more
openaire   +2 more sources

Partitioning a graph into two isomorphic pieces [PDF]

open access: possibleJournal of Graph Theory, 2003
AbstractA simple graph G has the neighbour‐closed‐co‐neighbour property, or ncc property, if for all vertices x of G, the subgraph induced by the set of neighbours of x is isomorphic to the subgraph induced by the set of non‐neighbours of x. We present characterizations of graphs with the ncc property via the existence of certain perfect matchings, and
FUNK, Martin   +3 more
openaire   +6 more sources

Transport Phenomena in Zeolites in View of Graph Theory and Pseudo-Phase Transition.

Small, 2020
Transport phenomena play an essential role in catalysis. While zeolite catalysis is widely applied in industrial chemical processes, its efficiency is often limited by the transport rate in the micropores of the zeolite.
Dali Cai   +3 more
semanticscholar   +1 more source

Relationship between Power Flow Transferring and Path Length using Graph Theory

2020 IEEE 1st China International Youth Conference on Electrical Engineering (CIYCEE), 2020
Unexpected power changes may lead to transmission line overload and even evolve into cascading breakout. To avoid this, the key is to analyze how the power flow transfers after disturbance.
Jiawei Yu, Ziqian Yang, M. Zhan
semanticscholar   +1 more source

Graph Neural Networks: Foundation, Frontiers and Applications

Knowledge Discovery and Data Mining, 2022
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the recent years. Graph neural networks, also known as deep learning on graphs, graph representation learning, or geometric deep learning, have become one of the fastest-
Lingfei Wu   +4 more
semanticscholar   +1 more source

Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes

Neural Information Processing Systems, 2023
Node-level random walk has been widely used to improve Graph Neural Networks. However, there is limited attention to random walk on edge and, more generally, on $k$-simplices.
Cai Zhou, Xiyuan Wang, Muhan Zhang
semanticscholar   +1 more source

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