Personne
William Trouleau
Cette personne n’est plus à l’EPFL
Publications associées (8)
A Variational Inference Approach to Learning Multivariate Wold Processes
Patrick Thiran, Matthias Grossglauser, Negar Kiyavash, Seyed Jalal Etesami, William Trouleau
Temporal point-processes are often used for mathematical modeling of sequences of discrete events with asynchronous timestamps. We focus on a class of temporal point-process models called multivariate Wold processes (MWP). These processes are well suited t ...
PMLR2021Learning Self-Exciting Temporal Point Processes Under Noisy Observations
Understanding the diffusion patterns of sequences of interdependent events is a central question for a variety of disciplines. Temporal point processes are a class of elegant and powerful models of such sequences; these processes have become popular across ...
EPFL2021Quantifying the Effects of Contact Tracing, Testing, and Containment Measures in the Presence of Infection Hotspots
Multiple lines of evidence at the individual and population level strongly suggest that infection hotspots, or superspreading events, where a single individual infects many others, play a key role in the transmission dynamics of COVID-19. However, most of ...
2020Learning Hawkes Processes Under Synchronization Noise
Patrick Thiran, Matthias Grossglauser, Negar Kiyavash, Seyed Jalal Etesami, William Trouleau
Multivariate Hawkes processes (MHP) are widely used in a variety of fields to model the occurrence of discrete events. Prior work on learning MHPs has only focused on inference in the presence of perfect traces without noise. We address the problem of lear ...
PMLR2019Learning Hawkes Processes from a Handful of Events
Patrick Thiran, Matthias Grossglauser, William Trouleau, Farnood Salehi
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 ...
2019Stochastic Optimal Control of Epidemic Processes in Networks
Utkarsh Upadhyay, William Trouleau
We approach the development of models and control strategies of susceptible-infected-susceptible (SIS) epidemic processes from the perspective of marked temporal point processes and stochastic optimal control of stochastic differential equations (SDEs) wit ...
2018Just One More: Modeling Binge Watching Behavior
Easy accessibility can often lead to over-consumption, as seen in food and alcohol habits. On video on-demand (VOD) services, this has recently been referred to as binge watching, where potentially entire seasons of TV shows are consumed in a single viewin ...
ACM Press2016Learning Hawkes Processes Under Synchronization Noise
Patrick Thiran, Matthias Grossglauser, Negar Kiyavash, Seyed Jalal Etesami, William Trouleau
Multivariate Hawkes processes (MHP) are widely used in a variety of fields to model the occurrence of discrete events. Prior work on learning MHPs has only focused on inference in the presence of perfect traces without noise. We address the problem of lear ...
MLR Press0