408 citations · 2.6k across the 52 of their papers we have counts for
52 papers
Ellipsoidal embeddings of graphs
Michaël Fanuel, Antoine Aspeel, Michael T. Schaub +1
Due to their flexibility to represent almost any kind of relational data, graph-based models have enjoyed a tremendous success over the past decades. While graphs are inherently on…
A model-based approach to meta-Reinforcement Learning: Transformers and tree search
Brieuc Pinon, Jean-Charles Delvenne, Raphaël Jungers
Meta-learning is a line of research that develops the ability to leverage past experiences to efficiently solve new learning problems. Meta-Reinforcement Learning (meta-RL) methods…
PAC-learning gains of Turing machines over circuits and neural networks
Brieuc Pinon, Raphaël Jungers, Jean-Charles Delvenne
A caveat to many applications of the current Deep Learning approach is the need for large-scale data. One improvement suggested by Kolmogorov Complexity results is to apply the min…
Flow stability for dynamic community detection
Alexandre Bovet, Jean-Charles Delvenne, Renaud Lambiotte
Many systems exhibit complex temporal dynamics due to the presence of different processes taking place simultaneously. An important task in such systems is to extract a simplified…
Severability of mesoscale components and local time scales in dynamical networks
Yun William Yu, Jean-Charles Delvenne, Sophia N. Yaliraki +1
A major goal of dynamical systems theory is the search for simplified descriptions of the dynamics of a large number of interacting states. For overwhelmingly complex dynamical sys…
State aggregations in Markov chains and block models of networks
Mauro Faccin, Michael T. Schaub, Jean-Charles Delvenne
We consider state-aggregation schemes for Markov chains from an information-theoretic perspective. Specifically, we consider aggregating the states of a Markov chain such that the…
Multi-scale Anomaly Detection on Attributed Networks
Leonardo Gutiérrez-Gómez, Alexandre Bovet, Jean-Charles Delvenne
Many social and economic systems can be represented as attributed networks encoding the relations between entities who are themselves described by different node attributes. Findin…
Network constraints on the mixing patterns of binary node metadata
Matteo Cinelli, Leto Peel, Antonio Iovanella +1
We consider the network constraints on the bounds of the assortativity coefficient, which measures the tendency of nodes with the same attribute values to be interconnected. The as…
Unsupervised Network Embedding for Graph Visualization, Clustering and Classification
Leonardo Gutiérrez-Gómez, Jean-Charles Delvenne
A main challenge in mining network-based data is finding effective ways to represent or encode graph structures so that it can be efficiently exploited by machine learning algorith…
Rock-Paper-Scissors Random Walks on Temporal Multilayer Networks
Martin Gueuning, Sibo Cheng, Renaud Lambiotte +1
We study diffusion on a multilayer network where the contact dynamics between the nodes is governed by a random process and where the waiting time distribution differs for edges fr…
The anatomy of Reddit: An overview of academic research
Alexey N. Medvedev, Renaud Lambiotte, Jean-Charles Delvenne
Online forums provide rich environments where users may post questions and comments about different topics. Understanding how people behave in online forums may shed light on the f…
Measuring the effect of node aggregation on community detection
Yérali Gandica, Adeline Decuyper, Christophe Cloquet +2
Many times the nodes of a complex network, whether deliberately or not, are aggregated for technical, ethical, legal limitations or privacy reasons. A common example is the geograp…
Multi-hop assortativities for networks classification
Leonardo Gutierrez Gomez, Jean-Charles Delvenne
Several social, medical, engineering and biological challenges rely on discovering the functionality of networks from their structure and node metadata, when it is available. For e…
Spectral clustering algorithms for the detection of clusters in block-cyclic and block-acyclic graphs
H. Van Lierde, T. W. S. Chow, J. -C. Delvenne
We propose two spectral algorithms for partitioning nodes in directed graphs respectively with a cyclic and an acyclic pattern of connection between groups of nodes. Our methods ar…
Structured networks and coarse-grained descriptions: a dynamical perspective
Michael T. Schaub, Jean-Charles Delvenne, Renaud Lambiotte +1
This chapter discusses the interplay between structure and dynamics in complex networks. Given a particular network with an endowed dynamics, our goal is to find partitions aligned…
Multiscale dynamical embeddings of complex networks
Michael T. Schaub, Jean-Charles Delvenne, Renaud Lambiotte +1
Complex systems and relational data are often abstracted as dynamical processes on networks. To understand, predict and control their behavior, a crucial step is to extract reduced…
Modelling structure and predicting dynamics of discussion threads in online boards
Alexey N. Medvedev, Jean-Charles Delvenne, Renaud Lambiotte
Internet boards are platforms for online discussions about a variety of topics. On these boards, individuals may start a new thread on a specific matter, or leave comments in an ex…
Different approaches to community detection
Martin Rosvall, Jean-Charles Delvenne, Michael T. Schaub +1
A precise definition of what constitutes a community in networks has remained elusive. Consequently, network scientists have compared community detection algorithms on benchmark ne…
Entrograms and coarse graining of dynamics on complex networks
Mauro Faccin, Michael T. Schaub, Jean-Charles Delvenne
Using an information theoretic point of view, we investigate how a dynamics acting on a network can be coarse grained through the use of graph partitions. Specifically, we are inte…
Positive semi-definite embedding for dimensionality reduction and out-of-sample extensions
Michaël Fanuel, Antoine Aspeel, Jean-Charles Delvenne +1
In machine learning or statistics, it is often desirable to reduce the dimensionality of a sample of data points in a high dimensional space . This paper introduces a…
Multiscale mixing patterns in networks
Leto Peel, Jean-Charles Delvenne, Renaud Lambiotte
Assortative mixing in networks is the tendency for nodes with the same attributes, or metadata, to link to each other. It is a property often found in social networks manifesting a…
Dynamics Based Features For Graph Classification
Leonardo Gutierrez Gomez, Benjamin Chiem, Jean-Charles Delvenne
Numerous social, medical, engineering and biological challenges can be framed as graph-based learning tasks. Here, we propose a new feature based approach to network classification…
Random Multi-Hopper Model. Super-Fast Random Walks on Graphs
Ernesto Estrada, Jean-Charles Delvenne, Naomichi Hatano +4
We develop a model for a random walker with long-range hops on general graphs. This random multi-hopper jumps from a node to any other node in the graph with a probability that dec…
The many facets of community detection in complex networks
Michael T. Schaub, Jean-Charles Delvenne, Martin Rosvall +1
Community detection, the decomposition of a graph into essential building blocks, has been a core research topic in network science over the past years. Since a precise notion of w…