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Patrick Thiran

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Publications associées (103)

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Mapping Human Whole-Brain Structural Networks with Diffusion MRI

Jean-Philippe Thiran, Patrick Thiran, Patric Hagmann, Reto Meuli, Xavier Gigandet, Maciej Kurant

Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodo ...

2007

Mining Democracy

Patrick Thiran, Matthias Grossglauser, Julien Pierre Sacha Herzen, Vincent Etter

Switzerland has a long tradition of direct democracy, which makes it an ideal laboratory for research on real-world politics. Similar to recent open government initiatives launched worldwide, the Swiss government regularly releases datasets related to stat ...

2014

On the robustness of the metric dimension of grid graphs to adding a single edge

Patrick Thiran, Gergely Odor

The metric dimension (MD) of a graph is a combinatorial notion capturing the minimum number of landmark nodes needed to distinguish every pair of nodes in the graph based on graph distance. We study how much the MD can increase if we add a single edge to t ...

2022

Reducing Sensor Requirements by Relaxing the Network Metric Dimension

Robin Jaccard, Paula Anette Mürmann, Patrick Thiran, Maximilien Claude Robert Dreveton

Source localization in graphs involves identifying the origin of a phenomenon or event, such as an epidemic outbreak or a misinformation source, by leveraging structural graph properties. One key concept in this context is the metric dimension, which quant ...

Association for Computing Machinery (ACM)2025

Why the Metric Backbone Preserves Community Structure

Charbel Chucri, Patrick Thiran, Matthias Grossglauser, Maximilien Claude Robert Dreveton

The metric backbone of a weighted graph is the union of all-pairs shortest paths. It is obtained by removing all edges

(u,v)

that are not the shortest path between

u

and

v

. In networks with well-separated communities, the metric backbone tends to pre ...

2024

Enhance & Explore: an Adaptive Algorithm to Maximize the Utility of Wireless Networks

Patrick Thiran, Ruben Merz, Julien Pierre Sacha Herzen, Adel Aziz

The goal of jointly providing efficiency and fairness in wireless networks can be seen as the problem of maximizing a given utility function. In contrast with wired networks, the capacity of wireless networks is typically time-varying and not known explici ...

2011

Balanced relay allocation on heterogeneous unstructured overlays

Patrick Thiran, Matthias Grossglauser, Xuan Hung Nguyen

Due to the increased usage of NAT boxes and firewalls, it has become harder for applications to establish direct connections seamlessly among two end-hosts. A recently, adopted proposal to mitigate this problem is to use relay nodes, end-hosts that act as ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2008

Self-Organization Properties of CSMA/CA Systems and Their Consequences on Fairness

Patrick Thiran, Olivier Dousse, Mathilde Durvy

Decentralized medium access control schemes for wireless networks based on CSMA/CA, such as the IEEE 802.11 protocol, are known to be unfair. In multihop networks, they can even favor some links to such an extent that the others suffer from virtually compl ...

Institute of Electrical and Electronics Engineers2009

Optimal performance of Graph Convolutional Networks on the Contextual Stochastic Block Model

Patrick Thiran, Guillaume Cyprien Dalle

For Graph Neural Networks, oversmoothing denotes the homogenization of vertex embeddings as the number of layers increases. To better understand this phenomenon, we study community detection with a linearized Graph Convolutional Network on the Contextual S ...

2024

On the Delays in Time-Varying Networks: Does Larger Service-Rate Variance Imply Larger Delays?

Patrick Thiran, Sébastien Christophe Henri

In all networks, link or route capacities fluctuate for multiple reasons, e.g., fading and multi-path effects on wireless channels, interference and contending users on a shared medium, varying loads in WAN routers, impedance changes on power-line channels ...

2018

War of Words II: Enriched Models of Law-Making Processes

Patrick Thiran, Matthias Grossglauser, Victor Kristof, Aswin Suresh

The European Union law-making process is an instance of a peer- production system. We mine a rich dataset of law edits and intro- duce models predicting their adoption by parliamentary committees. Edits are proposed by parliamentarians, and they can be in ...

ACM2021

Network Tomography on Correlated Links

Patrick Thiran, Aikaterini Argyraki, Denisa Gabriela Ghita

Network tomography establishes linear relationships between the characteristics of individual links and those of end-to-end paths. It has been proved that these relationships can be used to infer the characteristics of links from end-to-end measurements, p ...

2010

Netscope: Practical Network Loss Tomography

Patrick Thiran, Aikaterini Argyraki, Maciej Kurant, Xuan Hung Nguyen, Denisa Gabriela Ghita

We present Netscope, a tomographic technique that infers the loss rates of network links from unicast end-to-end measurements. Netscope uses a novel combination of first- and second-order moments of end-to-end measurements to identify and characterize the ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Launch Hard or Go Home! Predicting the Success of Kickstarter Campaigns

Patrick Thiran, Matthias Grossglauser, Vincent Etter

Crowdfunding websites such as Kickstarter are becoming increasingly popular, allowing project creators to raise hundreds of millions of dollars every year. However, only one out of two Kickstarter campaigns reaches its funding goal and is successful. It is ...

ACM2013

Interval consensus: from quantized gossip to voting

Martin Vetterli, Patrick Thiran, Florence Bénézit

We design distributed and quantized average consensus algorithms on arbitrary connected networks. By construction, quantized algorithms cannot produce a real, analog average. Instead, our algorithm reaches consensus on the quantized interval that contains ...

2009

Learning Hawkes Processes from a Handful of Events

Patrick Thiran, Matthias Grossglauser, Farnood Salehi, William Trouleau

Learning the causal-interaction network of multivariate Hawkes processes is a useful task in many applications. Maximum-likelihood estimation is the most common approach to solve the problem in the presence of long observation sequences. However, when only ...

2019

Layered Complex Networks

Patrick Thiran, Maciej Kurant

Many complex networks are only a part of larger systems, where a number of coexisting topologies interact and depend on each other. We introduce a layered model to facilitate the description and analysis of such systems. As an example of its application, w ...

2006

The Boolean Solution to the Congested IP Link Location Problem: Theory and Practice

Patrick Thiran, Xuan Hung Nguyen

Like other problems in network tomography or traffic matrix estimation, the location of congested IP links from end-to-end measurements requires solving a system of equations that relate the measurement outcomes with the variables representing the status o ...

2007

EZ-Flow: Removing Turbulence in IEEE 802.11 Wireless Mesh Networks without Message Passing

Patrick Thiran, Alexandre Fawal, Adel Aziz

Recent analytical and experimental work demonstrate that IEEE 802.11-based wireless mesh networks are prone to turbulence. Manifestations of such turbulence take the form of large buffer build-up at relay nodes, end-to-end delay fluctuations, and traffic c ...

2009

Error and Attack Tolerance of Layered Complex Networks

Patric Hagmann, Patrick Thiran, Maciej Kurant

Many complex systems may be described by not one but a number of complex networks mapped on each other in a multi-layer structure. Because of the interactions and dependencies between these layers, the state of a single layer does not necessarily reflect w ...

2007