Results 31 to 40 of about 484,377 (242)
The sinoatrial node, a heterogeneous pacemaker structure [PDF]
Cardiovascular Research, 2000 This article focuses on the regional heterogeneity of the mammalian sinoatrial (SA) node in terms of cell morphology, pacemaker activity, action potential configuration and conduction, densities of ionic currents (i(Na), i(Ca,L), i(to), i(K,r), i(K,s) and i(f)), expression of gap junction proteins (Cx40, Cx43 and Cx45), autonomic regulation, and ageing.
M R, Boyett, H, Honjo, I, Kodama
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Toward Understanding and Evaluating Structural Node Embeddings
ACM Transactions on Knowledge Discovery from Data, 2021 While most network embedding techniques model the proximity between nodes in a network, recently there has been significant interest in structural embeddings that are based on node equivalences , a notion rooted in sociology: equivalences or positions are collections of nodes that have ...
Junchen Jin +3 more
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struc2vec: Learning Node Representations from Structural Identity
, 2017 Structural identity is a concept of symmetry in which network nodes are identified according to the network structure and their relationship to other nodes.
Mikolov Tomas +3 more
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Data structure for node connectivity queries.
CoRR, 2021 Let κ(s,t) denote the maximum number of internally disjoint st-paths in an undirected graph G. We consider designing a data structure that includes a list of cuts, and answers the following query: given s,t ∈ V, determine whether κ(s,t) ≤ k, and if so, return a pointer to an st-cut of size ≤ k (or to a minimum st-cut) in the list.
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, 2007 We study structural properties of growing networks where both addition and deletion of nodes are possible. Our model network evolves via two independent processes.
Abramowitz M +16 more
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Deep Mutual Encode Model for Network Embedding From Structural Identity
IEEE Access, 2019 Network Embedding (NE) is one of the most popular learning methods in complex networks. It aims at learning the low-dimensional representations of nodes in networks and has been applied in a variety of network analytic tasks.
Hongyao Ke +6 more
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The overlapping community structure of structural brain network in young healthy individuals.
PLoS ONE, 2011 Community structure is a universal and significant feature of many complex networks in biology, society, and economics. Community structure has also been revealed in human brain structural and functional networks in previous studies. However, communities
Kai Wu +10 more
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IEEE Access, 2020 Node similarity is a significant basis for analyzing features in complex network. For complex network with directed weighted edge, the complexity of the relationship among nodes and the diversity of relationship weights make measure node similarity ...
Wanchang Jiang, Yinghui Wang
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On Exploring Node-Feature and Graph-Structure Diversities for Node Drop Graph Pooling
Neural Networks, 2023 14 pages, 14 ...
Chuang Liu 0008 +6 more
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STEPS - an approach for human mobility modeling [PDF]
, 2011 In this paper we introduce Spatio-TEmporal Parametric Stepping (STEPS) - a simple parametric mobility model which can cover a large spectrum of human mobility patterns.
A. Chaintreau +9 more
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