356 citations · 670 across the 13 of their papers we have counts for
14 papers
Community-Centers Identify Robust Biomarkers in High-Dimensional, Low-Sample-Size Gene Expression Data
Ruiqi Li, Te Bai, Renaud Lambiotte +4
High-dimensional, low-sample-size bulk gene expression data poses a fundamental challenge in transcriptomics, which typically includes tens of thousands of genes but relatively few…
Decomposing force fields as flows on graphs reconstructed from stochastic trajectories
Ramón Nartallo-Kaluarachchi, Paul Expert, David Beers +4
Disentangling irreversible and reversible forces from random fluctuations is a challenging problem in the analysis of stochastic trajectories measured from real-world dynamical sys…
A unified framework for Simplicial Kuramoto models
Marco Nurisso, Alexis Arnaudon, Maxime Lucas +4
Simplicial Kuramoto models have emerged as a diverse and intriguing class of models describing oscillators on simplices rather than nodes. In this paper, we present a unified frame…
Local dominance unveils clusters in networks
Dingyi Shi, Fan Shang, Bingsheng Chen +6
Clusters or communities can provide a coarse-grained description of complex systems at multiple scales, but their detection remains challenging in practice. Community detection met…
Connecting Hodge and Sakaguchi-Kuramoto: a mathematical framework for coupled oscillators on simplicial complexes
Alexis Arnaudon, Robert L. Peach, Giovanni Petri +1
We formulate a general Kuramoto model on weighted simplicial complexes where phases oscillators are supported on simplices of any order . Crucially, we introduce linear and non-…
Cycle Analysis of Directed Acyclic Graphs
Vaiva Vasiliauskaite, Tim S. Evans, Paul Expert
In this paper, we employ the decomposition of a directed network as an undirected graph plus its associated node metadata to characterise the cyclic structure found in directed net…
Modelling the Spread of Covid-19 on Malaysian Contact Networks for Practical Reopening Strategies in an Institutional Setting
Fatimah Abdul Razak, Paul Expert
Reopening strategies are crucial to balance efforts of economic revitalization and bringing back a sense of normalcy while mitigating outbreaks and effectively flattening the infec…
Geometric graphs from data to aid classification tasks with graph convolutional networks
Yifan Qian, Paul Expert, Pietro Panzarasa +1
Traditional classification tasks learn to assign samples to given classes based solely on sample features. This paradigm is evolving to include other sources of information, such a…
Quantifying the Alignment of Graph and Features in Deep Learning
Yifan Qian, Paul Expert, Tom Rieu +2
We show that the classification performance of graph convolutional networks (GCNs) is related to the alignment between features, graph, and ground truth, which we quantify using a…
A minimally invasive neurostimulation method for controlling epilepsy seizures
Malbor Asllani, Timoteo Carletti
Many coordination phenomena in Nature are grounded on a synchronisation regime. In the case of brain dynamics, such self-organised process allows the neurons of particular brain re…
Graph spectral characterisation of the XY model on complex networks
Paul Expert, Sarah de Nigris, Taro Takaguchi +1
There is recent evidence that the spin model on complex networks can display three different macroscopic states in response to the topology of the network underpinning the int…
Temporal stability of network partitions
Giovanni Petri, Paul Expert
We present a method to find the best temporal partition at any time-scale and rank the relevance of partitions found at different time-scales. This method is based on random walker…
Uncovering space-independent communities in spatial networks
Paul Expert, Tim Evans, Vincent D. Blondel +1
Many complex systems are organized in the form of a network embedded in space. Important examples include the physical Internet infrastucture, road networks, flight connections, br…
Self-similar correlation function in brain resting-state fMRI
Paul Expert, Renaud Lambiotte, Dante R. Chialvo +4
Adaptive behavior, cognition and emotion are the result of a bewildering variety of brain spatiotemporal activity patterns. An important problem in neuroscience is to understand th…