23 papers · ranked by Valyu relevance
Cedric E. Ginestet, Arnaud P. Fournel, Andrew Simmons
Comparing networks in neuroscience is hard, because the topological properties of a given network are necessarily dependent on the number of edges in that network. This problem arises in the analysis of both weighted and unweighted networks. The term density is often used in this context, in order to refer to the mean…
Sorour E. Amiri, Bijaya Adhikari, John Wenskovitch, Alexander Rodríguez + 3 more
'Alexander Rodríguez' 'Michelle Dowling' 'Chris North' 'B. Aditya Prakash'] Generating useful network summaries is a challenging and important problem with several applications like sensemaking, visualization, and compression. However, most of the current work in this space do not take human feedback into account while…
Dandan Guo, Long Tian, Minghe Zhang, Mingyuan Zhou + 1 more
Learning from set-structured data is a fundamental problem that has recently attracted increasing attention, where a series of summary networks are introduced to deal with the set input. In fact, many meta-learning problems can be treated as set-input tasks. Most existing summary networks aim to design different…
James P. Bagrow, Yong‐Yeol Ahn
The deluge of network datasets demands a standard way to effectively and succinctly summarize network datasets. Building on similar efforts to standardize the documentation of models and datasets in machine learning, here we propose network cards, short summaries of network datasets that can capture not only the basic…
Insuk Lee, Eiru Kim, Edward M. Marcotte
We find that the topologies of real world networks, such as those formed within human societies, by the Internet, or among cellular proteins, are dominated by the mode of the interactions considered among the individuals. Consequently, a major dichotomy in previously studied networks arises from modeling networks in…
Jonatan Frank, Marcel Hoffmann, Nicolas Lell, David Richerby + 1 more
Time Warp Authors: ['Jonatan Frank' 'Marcel Hoffmann' 'Nicolas Lell' 'David Richerby' 'Ansgar Scherp'] Summarizing web graphs is challenging due to the heterogeneity of the modeled information and its changes over time. We investigate the use of neural networks for lifelong graph summarization. Assuming we observe the…
Johan Hasselqvist, Niklas Helmertz, Mikael Kågebäck
In this paper, we present a model for generating summaries of text documents with respect to a query. This is known as querybased summarization. We adapt an existing dataset of news article summaries for the task and train a pointer-generator model using this dataset. The generated summaries are evaluated by measuring…
B.C.L. Lehmann, R.N. Henson, L. Geerligs, S.R. White
The brain can be modelled as a network with nodes and edges derived from a range of imaging modalities: the nodes correspond to spatially distinct regions and the edges to the interactions between them. Whole-brain connectivity studies typically seek to determine how network properties change with a given categorical…
Jacob A. Zavatone-Veth, Blake Bordelon, Cengiz Pehlevan
How can we make sense of large-scale recordings of neural activity across learning? Theories of neural network learning with their origins in statistical physics offer a potential answer: for a given task, there are often a small set of summary statistics that are sufficient to predict performance as the network…
Louis Raynal, Sixing Chen, Antonietta Mira, Jukka‐Pekka Onnela
Approximate Bayesian computation (ABC) is a simulation-based likelihood-free method applicable to both model selection and parameter estimation. ABC parameter estimation requires the ability to forward simulate datasets from a candidate model, but because the sizes of the observed and simulated datasets usually need to…
Viplove Arora, Mario Ventresca
Complex networks can model a wide range of complex systems in nature and society, and many algorithms (network generators) capable of synthesizing networks with few and very specific structural characteristics (degree distribution, average path length, etc.) have been developed. However, there remains a significant…
Rakesh Sengupta
Computing summary or ensemble statistics of a visual scene is often automatic and a hard necessity for stable perceptual life of a cognitive agent. Although computationally the process should be as simple as applying a filter as it were to a perceived scene, the issue of mechanism of summary statistics is complicated…
Rogini Runghen, Tina Eliassi-Rad, Daniel I. Bolnick
Weighted Gene Co-expression Network Analysis (WGCNA) is routinely applied to pooled datasets from multiple biological populations, genotypes, or treatment groups, implicitly assuming a shared module structure across groups. While the distortion of pairwise correlations by pooling heterogeneous groups is well…
Benjamin Ries, Richard J Gowers, James RB Eastwood, Irfan Alibay + 4 more
Alchemical free energy campaigns can be planned using graph theory by building up networks that contain nodes representing molecules that are connected by possible transformations as edges. We introduce Konnektor, an open-source Python package, for systematically planning, modifying, and analyzing free energy…
D. Morrison, M. Bedinger, L. Beevers, K. McClymont
Network analysis is a useful tool to analyse the interactions and structure of graphs that represent the relationships among entities, such as sectors within an urban system. Connecting entities in this way is vital in understanding the complexity of the modern world, and how to navigate these complexities during an…
Matthew Bailey, Mark Wilson
One of the critical tools of persistent homology is the persistence diagram. We demonstrate the applicability of a persistence diagram showing the existence of topological features (here rings in a 2D network) generated over time instead of space as a tool to analyse trajectories of biological networks. We show how the…
Jennifer M. Schopf, Katrina Turner, Dan Doyle, Andrew Lake + 2 more
'Jason Leigh' 'Brian L. Tierney'] Data sharing is required for research collaborations, but effective data transfer performance continues to be difficult to achieve. The NetSage Measurement and Analysis Framework can assist in understanding research data movement. It collects a broad set of monitoring data and builds…
Jana Weber, Pietro Lio’, Alexei Lapkin
Networks of chemical reactions represent relationships between molecules within chemical supply chains and promise to enhance planning of multi-step synthesis routes from bio-renewable feedstocks. This study aims to identify strategic molecules in chemical reaction networks that may potentially play a significant role…
Guillaume Péron
The graph transitivity measures the probability that adjacent vertices in a network are interconnected, thus revealing the existence of tightly connected neighborhoods playing a role in information and pathogen circulation. The graph transitivity is usually computed for dichotomized networks, therefore focusing on…
Sergio Pablo-García, Raúl Pérez-Soto, Albert Sabadell-Rendón, Diego Garay-Ruiz + 2 more
In the study of chemical reactions, visualizing reaction networks is pivotal for identifying crucial compounds and reactions. Traditional methods, such as network schematics and reaction path linear plots, often struggle to effectively represent complex reaction networks due to their size and intricate connectivity.…
Jesús Antonio Puente Fernández, Luis Javier García Villalba, Tai-Hoon Kim
'Tai-Hoon Kim'] Nowadays, different protocols coexist in Internet that provides services to users. Unfortunately, control decisions and distributed management make it hard to control networks. These problems result in an inefficient and unpredictable network behaviour. Software Defined Networks (SDN) is a new concept…
Santiago Morandi, Oliver Loveday, Tim Renningholtz, Sergio Pablo-García + 6 more
Process optimization in heterogeneous catalysis relies on the control of competing reactions. The reaction mechanisms based on chemical knowledge can be evaluated via density functional theory unveiling experimental catalytic trends. However, this approach finds its limits when applied to complex reaction networks or…
Matthew H. J. Bailey, Mark Wilson
Networks of biopolymers occur often in nature, and are vulnerable to damage over time. In this work, a coarse grained model of collagen IV molecules is applied in a 2D hexagonal network and the mechanisms by which these networks can rupture are explored. The networks are stretched linearly in order to study their…