214 citations · 676 across the 14 of their papers we have counts for
15 papers
Information maximization for a broad variety of multi-armed bandit games
Alex Barbier-Chebbah, Christian L. Vestergaard, Jean-Baptiste Masson
Information and free-energy maximization are physics principles that provide general rules for an agent to optimize actions in line with specific goals and policies. These principl…
Compression-based inference of network motif sets
Alexis Bénichou, Jean-Baptiste Masson, Christian L. Vestergaard
Physical and functional constraints on biological networks lead to complex topological patterns across multiple scales in their organization. A particular type of higher-order netw…
Approximate information maximization for bandit games
Alex Barbier-Chebbah, Christian L. Vestergaard, Jean-Baptiste Masson +1
Entropy maximization and free energy minimization are general physical principles for modeling the dynamics of various physical systems. Notable examples include modeling decision-…
Approximate information for efficient exploration-exploitation strategies
Alex Barbier-Chebbah, Christian L. Vestergaard, Jean-Baptiste Masson
This paper addresses the exploration-exploitation dilemma inherent in decision-making, focusing on multi-armed bandit problems. The problems involve an agent deciding whether to ex…
Variational inference of fractional Brownian motion with linear computational complexity
Hippolyte Verdier, François Laurent, Alhassan Cassé +2
We introduce a simulation-based, amortised Bayesian inference scheme to infer the parameters of random walks. Our approach learns the posterior distribution of the walks' parameter…
Gillespie algorithms for stochastic multiagent dynamics in populations and network
Naoki Masuda, Christian L. Vestergaard
Many multiagent dynamics, including various collective dynamics occurring on networks, can be modeled as a stochastic process in which the agents in the system change their state o…
Learning physical properties of anomalous random walks using graph neural networks
Hippolyte Verdier, Maxime Duval, François Laurent +3
Single particle tracking allows probing how biomolecules interact physically with their natural environments. A fundamental challenge when analysing recorded single particle trajec…
Statistical Tests for Force Inference in Heterogeneous Environments
Alexander S. Serov, François Laurent, Charlotte Floderer +5
We devise a method to detect and estimate forces in a heterogeneous environment based on experimentally recorded stochastic trajectories. In particular, we focus on systems modeled…
Randomized reference models for temporal networks
Laetitia Gauvin, Mathieu Génois, Márton Karsai +4
Many dynamical systems can be successfully analyzed by representing them as networks. Empirically measured networks and dynamic processes that take place in these situations show h…
Impact of spatially constrained sampling of temporal contact networks on the evaluation of the epidemic risk
Christian L. Vestergaard, Eugenio Valdano, Mathieu Génois +3
The ability to directly record human face-to-face interactions increasingly enables the development of detailed data-driven models for the spread of directly transmitted infectious…
Optimizing experimental parameters for tracking of diffusing particles
Christian L. Vestergaard
We describe how a single-particle tracking experiment should be designed in order for its recorded trajectories to contain the most information about a tracked particle's diffusion…
Temporal Gillespie algorithm: Fast simulation of contagion processes on time-varying networks
Christian L. Vestergaard, Mathieu Génois
Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The…
Compensating for population sampling in simulations of epidemic spread on temporal contact networks
Mathieu Génois, Christian L. Vestergaard, Ciro Cattuto +1
Data describing human interactions often suffer from incomplete sampling of the underlying population. As a consequence, the study of contagion processes using data-driven models c…
How memory generates heterogeneous dynamics in temporal networks
Christian L. Vestergaard, Mathieu Génois, Alain Barrat
Empirical temporal networks display strong heterogeneities in their dynamics, which profoundly affect processes taking place on these networks, such as rumor and epidemic spreading…
Data on face-to-face contacts in an office building suggests a low-cost vaccination strategy based on community linkers
Mathieu Génois, Christian L. Vestergaard, Julie Fournet +3
Empirical data on contacts between individuals in social contexts play an important role in providing information for models describing human behavior and how epidemics spread in p…