output
20042026
most citedA regression-based Monte Carlo method to solve backward stochastic differential equations

425 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2021Show all

14 papers · 1 filter

cs.LG2021

Deep Surrogate for Direct Time Fluid Dynamics

Lucas Meyer, Louen Pottier, Alejandro Ribes +1

The ubiquity of fluids in the physical world explains the need to accurately simulate their dynamics for many scientific and engineering applications. Traditionally, well establish…

math.ST2021

Consistency of the maximum likelihood estimator in hidden Markov models with trends

Luc Lehéricy, Augustin Touron

A hidden Markov model with trends is a hidden Markov model whose emission distributions are translated by a trend that depends on the current hidden state and on the current time.…

eess.SY2021★ 3 cited

Impact of Strategic Electric Vehicles Driving Behavior on the Grid

Benoît Sohet, Yezekael Hayel, Olivier Beaude +1

In the context of transport electrification, a model coupling Electric Vehicles (EV) driving and charging decisions is considered. While a Traffic Assignment Problem (TAP) is consi…

cs.GT2021★ 3 cited

Learning Pure Nash Equilibrium in Smart Charging Games

Benoît Sohet, Yezekael Hayel, Olivier Beaude +1

Reinforcement Learning Algorithms (RLA) are useful machine learning tools to understand how decision makers react to signals. It is known that RLA converge towards the pure Nash Eq…

stat.AP2021

Hierarchical transfer learning with applications for electricity load forecasting

Anestis Antoniadis, Solenne Gaucher, Yannig Goude

The recent abundance of data on electricity consumption at different scales opens new challenges and highlights the need for new techniques to leverage information present at finer…

math.OC2021

Multi-stage Stochastic Alternating Current Optimal Power Flow with Storage: Bounding the Relaxation Gap

Maxime Grangereau, Wim van Ackooij, Stéphane Gaubert

We propose a generic multistage stochastic model for the Alternating Current Optimal Power Flow (AC OPF) problem for radial distribution networks, to account for the random electri…

stat.ML2021

Surrogate-based variational data assimilation for tidal modelling

Rem-Sophia Mouradi, Cédric Goeury, Olivier Thual +2

Data assimilation (DA) is widely used to combine physical knowledge and observations. It is nowadays commonly used in geosciences to perform parametric calibration. In a context of…

cond-mat.mtrl-sci2021

Ultrasonic monitoring of stress and cracks of the 1/3 scale mock-up of nuclear reactor concrete containment structure

Qi Xue, Eric Larose, Ludovic Moreau +3

To evaluate the stress level and damage of a reinforced concrete containment wall and its reaction to pressure variations, we implemented successive ultrasonic experiments on the e…

eess.SY2021★ 12 cited

Optimal Transmission Topology for Facilitating the Growth of Renewable Power Generation

Emily Little, Sandrine Bortolotti, Jean-Yves Bourmaud +2

Transmission topology control is a tool used by system operators in the role of a control action taken into account as a preventive or corrective action relative to a specific outa…

math.OC2021★ 1 cited

Chance constrained problems: a bilevel convex optimization perspective

Yassine Laguel, Jérôme Malick, Wim Ackooij

Chance constraints are a valuable tool for the design of safe decisions in uncertain environments; they are used to model satisfaction of a constraint with a target probability. Ho…

econ.EM2021★ 6 cited

Extreme dependence for multivariate data

Damien Bosc, Alfred Galichon

This article proposes a generalized notion of extreme multivariate dependence between two random vectors which relies on the extremality of the cross-covariance matrix between thes…

math.OC2021★ 1 cited

On the Convexity of Level-sets of Probability Functions

Yassine Laguel, Wim van Ackooij, Jérôme Malick +1

In decision-making problems under uncertainty, probabilistic constraints are a valuable tool to express safety of decisions. They result from taking the probability measure of a gi…

stat.ML2021

Making the most of your day: online learning for optimal allocation of time

Etienne Boursier, Tristan Garrec, Vianney Perchet +1

We study online learning for optimal allocation when the resource to be allocated is time. %Examples of possible applications include job scheduling for a computing server, a drive…

math.OC2021★ 16 cited

Neural networks-based algorithms for stochastic control and PDEs in finance

Maximilien Germain, Huyên Pham, Xavier Warin

This paper presents machine learning techniques and deep reinforcement learningbased algorithms for the efficient resolution of nonlinear partial differential equations and dynamic…