Pairwise Interaction Pattern in the Weighted Communication Network

Interaction Energy Based Protein Structure Networks - Cell Press

In the second case, we have elucidated the features of communication paths in proteins from the energy weighted networks. We have extensively discussed specific ...

It is found that the bursty trains usually evolve for pairs of individuals rather than for the ego and his/her several neighbours, thus burstiness is a ...

Using bipartite to describe and plot two-mode networks in R

weighted nestedness, or more specifically 'weighted interaction nestedness estimator'. (WINE), with 1 indicating perfected nestedness (thus exactly opposite ...

Full article: Network analysis: a brief overview and tutorial

Health psychology research examines how the complex interactions between biological, psychological, and social factors influence health and ...

Higher-Order Dynamics in Protein Interaction Networks - bioRxiv

graph model considers only pairwise interactions (i.e. edges between two proteins at ... We constructed a weighted interaction network model, as-.

Networks beyond pairwise interactions: Structure and dynamics

... model, с. 397; Ke; Ahn, Hypergraph spectral clustering in the weighted stochastic block model, IEEE J. Sel. Top. Signal Process., № 12, с. 959 https://doi.org ...

What Are Higher-Order Networks? | SIAM Review

network interactions between nodes are encoded in a directed, weighted ... tions Gk characterize the pairwise network interactions (cf. (5.1)) ...

A new method to measure complexity in binary or weighted ...

Network or graph theory is of increasing importance for the analysis of biological systems. This may comprise protein interaction networks [1], ...

Dynamics on higher-order networks: a review - Journals

In the above, we have already discussed how temporal higher-order interaction patterns modulate the discrete dynamics of social contagion [82].

Temporal patterns of communication in social networks - e-Archivo

network and by analyzing the role of temporal activity patterns of human interaction in the description and modeling of real social networks.

Edges in brain networks: Contributions to models of structure and ...

For such structural paths, its constituent edges and edge weights should reflect the cost or capacity of communication between nodes, such as ...

Intralayer and interlayer synchronization in multiplex network with ...

These beyond pairwise interactions are preferably modeled by hypergraphs, where hyperedges represent higher-order interactions between a set of ...

Computer Science - oalib

Pairwise interaction pattern in the weighted communication network · Xiao-Ke Xu,Jian-Bo Wang,Ye Wu,Michael Small · Broadcasters and Hidden Influentials in ...

A pairwise strategic network formation model with group heterogeneity

This study considers a network formation model in which each dyad of agents strategically determines the link status.

δ-MAPS: from spatio-temporal data to a weighted and lagged ...

After we identify all domains, δ-MAPS infers a functional network between them. Different domains may have correlated activity, potentially at a ...

Maximally informative pairwise interactions in networks

We will work in the context of neural networks, where the neurons communicate by firing voltage pulses commonly referred to as “spikes” 关15兴.

Nodal and Matrix Analyses of Communication Patterns in Small ...

In this ideal network, the pattern of interaction among group members is symmetrical and equal. Since we know the number of total interactions among group ...

NeurIPS 2024 Papers

ReMAP: Neural Model Reprogramming with Network Inversion and Retrieval-Augmented Mapping for Adaptive Motion Forecasting · QUEST: Quality-Aware Metropolis ...

Is it Really Over for LLMs? [Thoughts] - by Devansh

The statement that “neural networks can't solve everything alone” is very different from “Deep Learning is Hitting a Wall”. The subtitle implies ...

Maximally informative pairwise interactions in networks

We show that the optimal pairwise interactions are on average zero for Gaussian and uniformly distributed inputs, whereas they are nonzero for ...