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Conventional studies of network growth models mainly look at the steady state degree distribution of the graph. Often long time behavior is considered, hence the initial condition is ignored. In this contribution, the time evolution of the…

Physics and Society · Physics 2013-05-10 Babak Fotouhi , Michael Rabbat

We study the tailoring of structured random graph ensembles to real networks, with the objective of generating precise and practical mathematical tools for quantifying and comparing network topologies macroscopically, beyond the level of…

Disordered Systems and Neural Networks · Physics 2015-05-13 A. Annibale , A. C. C. Coolen , L. P. Fernandes , F. Fraternali , J. Kleinjung

Source code spends most of its time in a broken or incomplete state during software development. This presents a challenge to machine learning for code, since high-performing models typically rely on graph structured representations of…

Machine Learning · Computer Science 2021-06-01 Xuechen Li , Chris J. Maddison , Daniel Tarlow

It is challenging for generative models to learn a distribution over graphs because of the lack of permutation invariance: nodes may be ordered arbitrarily across graphs, and standard graph alignment is combinatorial and notoriously…

Social and Information Networks · Computer Science 2023-01-27 Kimia Shayestehfard , Dana Brooks , Stratis Ioannidis

Specify a randomized algorithm that, given a very large graph or network, extracts a random subgraph. What can we learn about the input graph from a single subsample? We derive laws of large numbers for the sampler output, by relating…

Statistics Theory · Mathematics 2017-10-13 Peter Orbanz

We introduce a family of one-dimensional geometric growth models, constructed iteratively by locally optimizing the tradeoffs between two competing metrics, and show that this family is equivalent to a family of preferential attachment…

Disordered Systems and Neural Networks · Physics 2007-05-23 N. Berger , C. Borgs , J. T. Chayes , R. M. D'Souza , R. D. Kleinberg

Graphs are ubiquitous in social networks and biochemistry, where Graph Neural Networks (GNN) are the state-of-the-art models for prediction. Graphs can be evolving and it is vital to formally model and understand how a trained GNN responds…

Machine Learning · Computer Science 2024-03-12 Yazheng Liu , Xi Zhang , Sihong Xie

The object-oriented class is, in general, the most utilized element in programming and modeling. It is employed throughout the software development process, from early domain analysis phases to later maintenance phases. A class diagram…

Software Engineering · Computer Science 2017-10-03 Sabah Al-Fedaghi

This research analyzes complex networks in open-source software at the inter-package level, where package dependencies often span across projects and between development groups. We review complex networks identified at ``lower'' levels of…

Software Engineering · Computer Science 2007-05-23 Nathan LaBelle , Eugene Wallingford

Existing studies on the degree correlation of evolving networks typically rely on differential equations and statistical analysis, resulting in only approximate solutions due to inherent randomness. To address this limitation, we propose an…

Computation · Statistics 2024-06-13 Yue Xiao , Xiaojun Zhang

Designing algorithms that generate networks with a given degree sequence while varying both subgraph composition and distribution of subgraphs around nodes is an important but challenging research problem. Current algorithms lack control of…

Physics and Society · Physics 2015-12-07 Martin Ritchie , Luc Berthouze , Istvan Z Kiss

The in-degree and out-degree distributions of a growing network model are determined. The in-degree is the number of incoming links to a given node (and vice versa for out-degree. The network is built by (i) creation of new nodes which each…

Statistical Mechanics · Physics 2009-10-31 P. L. Krapivsky , G. J. Rodgers , S. Redner

Dynamical processes on complex networks such as information propagation, innovation diffusion, cascading failures or epidemic spreading are highly affected by their underlying topologies as characterized by, for instance, degree-degree…

Data Analysis, Statistics and Probability · Physics 2013-03-05 Mathias Raschke , Markus Schläpfer , Konstantinos Trantopoulos

Leaves, i.e., vertices of degree one, can play a significant role in graph structure, especially in sparsely connected settings in which leaves often constitute the largest fraction of vertices. We consider a leaf-based counterpart of the…

Statistical Mechanics · Physics 2025-11-07 Harrison Hartle , P. L. Krapivsky

In real world domains, most graphs naturally exhibit a hierarchical structure. However, data-driven graph generation is yet to effectively capture such structures. To address this, we propose a novel approach that recursively generates…

Machine Learning · Computer Science 2023-06-01 Mahdi Karami , Jun Luo

Topology identification and inference of processes evolving over graphs arise in timely applications involving brain, transportation, financial, power, as well as social and information networks. This chapter provides an overview of graph…

Signal Processing · Electrical Eng. & Systems 2025-12-12 Gonzalo Mateos , Yanning Shen , Georgios B. Giannakis , Ananthram Swami

Large organizations have diverse product offerings to meet various business needs. To increase revenue, its common these days to offer software products as integrated product suite(s) rather than individual products. Creating and…

Software Engineering · Computer Science 2017-10-03 Sai Anirudh Karre , Y. Raghu Reddy

Call graphs depict the static, caller-callee relation between "functions" in a program. With most source/target languages supporting functions as the primitive unit of composition, call graphs naturally form the fundamental control flow…

Software Engineering · Computer Science 2016-11-17 Ganesh M. Narayan , K. Gopinath , V. Sridhar

Software metric plays a vital role in quantitative assessment of any specific software development methodology and its impact on the maintenance of software. It can also be used to indicate the degree of interdependence among the components…

Software Engineering · Computer Science 2020-12-02 Parthipan S , Senthil Velan S , Chitra Babu

The evolution of two species with different fitness is investigated on degree-heterogeneous graphs. The population evolves either by one individual dying and being replaced by the offspring of a random neighbor (voter model (VM) dynamics)…

Populations and Evolution · Quantitative Biology 2009-11-13 T. Antal , S. Redner , V. Sood