Jonathan Viquerat

According to our database, Jonathan Viquerat authored at least 16 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Multi-Grid Graph Neural Networks with Self-Attention for Computational Mechanics.

Paul Garnier, Jonathan Viquerat, Elie Hachem

CoRR, 2024

Beacon, a lightweight deep reinforcement learning benchmark library for flow control.

Jonathan Viquerat, Philippe Meliga, Pablo Jeken, Elie Hachem

CoRR, 2024

2023

Policy-based optimization: single-step policy gradient method seen as an evolution strategy.

Jonathan Viquerat, Régis Duvigneau, P. Meliga, Alexander Kuhnle, Elie Hachem

Neural Comput. Appl., 2023

Parallel bootstrap-based on-policy deep reinforcement learning for continuous flow control applications.

Jonathan Viquerat, Elie Hachem

CoRR, 2023

2022

A twin-decoder structure for incompressible laminar flow reconstruction with uncertainty estimation around 2D obstacles.

J. Chen, Jonathan Viquerat, F. Heymes, Elie Hachem

Neural Comput. Appl., 2022

Dynamic metasurface control using Deep Reinforcement Learning.

Ying Zhao, Liang Li, Stéphane Lanteri, Jonathan Viquerat

Math. Comput. Simul., 2022

2021

Direct shape optimization through deep reinforcement learning.

Jonathan Viquerat, Jean Rabault, Alexander Kuhnle, Hassan Ghraieb, Aurélien Larcher, Elie Hachem

J. Comput. Phys., 2021

Deep reinforcement learning for the control of conjugate heat transfer.

Elie Hachem, Hassan Ghraieb, Jonathan Viquerat, Aurélien Larcher, P. Meliga

J. Comput. Phys., 2021

2020

Optimization and passive flow control using single-step deep reinforcement learning.

Hassan Ghraieb, Jonathan Viquerat, Aurélien Larcher, P. Meliga, Elie Hachem

CoRR, 2020

2019

Direct shape optimization through deep reinforcement learning.

Jonathan Viquerat, Jean Rabault, Alexander Kuhnle, Hassan Ghraieb, Elie Hachem

CoRR, 2019

A review on Deep Reinforcement Learning for Fluid Mechanics.

Paul Garnier, Jonathan Viquerat, Jean Rabault, Aurélien Larcher, Alexander Kuhnle, Elie Hachem

CoRR, 2019

2018

Simulation of three-dimensional nanoscale light interaction with spatially dispersive metals using a high order curvilinear DGTD method.

Nikolai Schmitt, Claire Scheid, Jonathan Viquerat, Stéphane Lanteri

J. Comput. Phys., 2018

2017

Analysis of a Generalized Dispersive Model Coupled to a DGTD Method with Application to Nanophotonics.

Stéphane Lanteri, Claire Scheid, Jonathan Viquerat

SIAM J. Sci. Comput., 2017

2016

A DGTD method for the numerical modeling of the interaction of light with nanometer scale metallic structures taking into account non-local dispersion effects.

Nikolai Schmitt, Claire Scheid, Stéphane Lanteri, Antoine Moreau, Jonathan Viquerat

J. Comput. Phys., 2016

2015

A 3D curvilinear discontinuous Galerkin time-domain solver for nanoscale light-matter interactions.

Jonathan Viquerat, Claire Scheid

J. Comput. Appl. Math., 2015

2014

A parallel non-conforming multi-element DGTD method for the simulation of electromagnetic wave interaction with metallic nanoparticles.

Raphaël Léger, Jonathan Viquerat, Clément Durochat, Claire Scheid, Stéphane Lanteri

J. Comput. Appl. Math., 2014