WARIN Xavier

StorageAndMachineLearningArxiv

WARIN Xavier

The STochastic OPTimization library (StOpt)

https://gitlab.com/stochastic-control/StOpt

• "Distribution of a Stochastic Control Algorithm Applied to Gas Storage Valuation " (with C. Makassikis, S. Vialle) The 7th International Symposium on Signal Processing and Information Technology (ISSPIT-2007), IEEE Computer Society Press ,2007 [Publications] [2007]
   isspit-07-it_1714-makassikis-vialle-warin
• "A N-dimensional Stochastic Control Algorithm for Electricity Asset Management on PC cluster and Blue Gene Supercomputer" (with S Vialle, P Mercier) Workshop on State-of-the-Art in Scientific and Parallel Computing. Maximilien Germain,​_NTNU, Trondheim, NorwayMay 13-16, 2008 [Publications] [2008]
   para-2008-viallewarinmercier
• "Large Scale Distribution of Stochastic Control Algorithms for Financial Applications" (with C. Makassikis, S. Vialle), PDCoF08, pages 1-8, 2008-04 [Publications] [2008]
   pdcof-2008-makassikis-vialle-warin
• "Stochastic control optimization & simulation applied to energy management: From 1-D to N-D problem distributions, on clusters, supercomputers and Grids " (with S. Vialle, C. Makassikis, and P. Mercier) Grid@Mons conference, 2008 [Publications] [2008]
   lncs_warin_vialle_mercier
• "Large Scale Experiment and Optimization of a Distributed Stochastic Control Algorithm. Application to Energy Management Problems" (with P. Vezolle, S.Vialle) Workshop on Large-Scale Parallel Processing (LSPP 2009). Friday, May 29, 2009, Rome, Italy. [Publications] [2009]
   vezollewarinvialle_lspp_2009
• "Valuation of a powerplant under production constraints and markets incompleteness " (with A. Porchet, N. Touzi) Mathematical Methods of Operations research, Volume 70, Number 1 , pp 47-75, 2009. [Publications] [2009]
   ptwmmor
• "Design and Experimentation of a Large Scale Distributed Stochastic Control Algorithm Applied to Energy Management Problems" (with S Vialle) SBN 978-953-307-121-3, InTech, August 2010 [Articles de presse] [2010]
   chapter-mariva
• "A finite dimensional approximation for pricing moving average options" (with M Bernhart, P Tankov) SIAM Journal of Financial Mathematics Vol 2, pp 989-1013, 2011 [Publications] [2011]
   ma_options_r1
• " A Probabilistic Numerical Scheme for Fully Nonlinear PDEs " (with A. Fahim, N. Touzi) The Annals of Applied Probability, Vol 21, No 4, 1322-1364 [Publications] [2011]
   fahimtouziwarin-6avril2010
• "FT-GReLoSSS a Skeletal-Based Approach towards Application Parallelization and Low-Overhead Fault Tolerance" (with C. Makassikis, S Vialle), Proceedings of the 20th International Euromicro Conference PDP, 2012 [Publications] [2012]
  pdp2012_submission
• "Hedging swing contract on gas market" [Publications] [2012]
   swinggashedging
• "Gas storage hedging" , Numerical methods in finance, Springer [Publications] [2012]
   articlehedgingstockagegaz
• Swing option valuation : a BSDE with constrainted jumps approach" (with M Bernhart, H Pham, P Tankov) ,Numerical methods in finance, Springer  [Publications] [2012]
   swing_cjbsde_final_bptw
• "Monte-Carlo valorisation of American options: facts and new algorithms to improve existing methods" (with B Bouchard) Numerical methods in finance  [Publications] [2012]
   bouchardwarin
• Adaptive sparse grids for time dependent Hamilton-Jacobi-Bellman equations in stochastic control [Publications] [2014]
   hjb_sparse
• "Optimal Liquidity management and Hedging in the presence of a non-predictable investment opportunity" (with S. Villeneuve) Mathematics and Financial Economics (2014) 8: 193-227  [Publications] [2014]
   idei_osiris_optimalliquidity_version17122012
• "Liquidity Management with Decreasing-returns-to-scale and Secured Credit Line" with Erwan Pierre and Stéphane Villeneuve, Finance and Stochastics,October 2016, Volume 20, Issue 4, pp 809–854
   fs14-2610-2ndeversion
• "Numerical methods for the quadratic hedging problem in Markov models with jumps" (with C. De Franco, P. Tankov), Journal of Computational Finance, Volume 19, Number 2  [Publications] [2015]
   numerical_methods_for_the_quadratic_hedging_problem_in_markov_models_with_jumps_r2v3
• "Some non monotone schemes for time dependent Hamilton-Jacobi-Bellman equations in stochastic control", Journal of Scientific Computing, june 2015, pp 1-26 [Publications] [2015]
   hjb_jsc
• "Numerical approximation of a cash-constrained firm value with investment opportunities" (with Erwan Pierre, Stéphane Villeneuve),  SIAM Journal on Financial Mathematics , vol 8, issue 1  [2017]
   numericalapproximationsingular
• "Branching diffusion representation of semilinear PDEs and Monte Carlo approximation" with Pierre Henry-Labordère, Nizar Touzi , Nadia Oudjane, Xiaolu Tan, Annales de l’Institut Henri Poincaré Probabilité Statistiques , Volume 55, Number 1 (2019), 184-210.  [2019]
   Branching_Semilinear_rev
• "Unbiased Monte Carlo estimate of stochastic differential equations expectations", with M. Doumbia and N. Oudjane, ESAIM P&S ,  21 (2017) 56-87 [Publications] [2017]
   BranchOW2016_Final
• "The Asset Liability Management problem of a nuclear operator : a numerical stochastic optimization approach",  [Publications] [2016] alm_publication
• "Variations on branching methods for non linear PDEs" , 2017,  VariationsOnBranching
• "On conditional cuts for Stochastic Dual Dynamic Programming",  2019, with Wim Van-Ackooij, EURO Journal on Computational Optimization 8.2 (2020): 173-199  CondCuts_SDDP_vanAckooij_Warin
• "Numerical approximation of BSDEs using local polynomial drivers and branching processes" , with Bruno Bouchard, Xiaolu Tan, Yiyi Zou, 2017, Monte Carlo Methods and Applications, 2017, vol. 23, no 4, p. 241-263   BTWZ1
• "Numerical approximation of general Lipschitz BSDEs with branching processes", with Bruno Bouchard, Xiaolu Tan, CEMRACS 2017 - Numerical methods for stochastic models: control, uncertainty quantification, mean-field, ESAIM: Proceedings and Surveys, Volume 65  , p 309 - 329, (2019)    BTW17
• "Variance optimal hedging with application to Electricity markets"   in Journal Of Computational Finance, volume 23, number 3, dec 2019   varHedging
• "Fast and stable multivariate kernel density estimation by fast sum updating", with Nicolas Langrené, Journal of Computational and Graphical Statistics ,Volume 28, 2019 - Issue 3, Pages 596-608 ,  fastKDE_JCGS_final
• "Regression Monte Carlo for microgrid management", with  Clémence Alasseur, Alexandro Balata, Sahar Ben Aziza, Aditya Maheshwari, Peter Tankov,  CEMRACS 2017 - Numerical methods for stochastic models: control, uncertainty quantification, mean-field, ESAIM: Proceedings and Surveys, Volume 65 , p 46 - 67, (2019) microgrid_proceedings_14092018
• "Option valuation and hedging using asymmetric risk function: asymptotic optimality through fully nonlinear Partial Differential Equations", with Emmanuel gobet and Isaque Pimentel,  Finance Stoch (2020). https://doi.org/10.1007/s00780-020-00428-1 ,  paperAsymptotic
• "Nesting Monte Carlo for high-dimensional Non Linear PDEs" , Monte Carlo Methods and Applications, volume 24, issue 4, 2018 ,  MCPDE_arxiv
• "Monte Carlo for high-dimensional degenerated SemiLinear and Full Non Linear PDEs", 2018, , MC2PDE_Arxiv
• "Machine Learning for semi linear PDEs" with  Chan-Wai-Nam, Q., Mikael, Journal of Scientific Computing, 79(3), 1667-1712,  2019, https://doi.org/10.1007/s10915-019-00908-3  ‡Machine_Learning_and_nesting_Monte_Carlo_for_semi_linear_PDEs
• "Some non monotone schemes for Hamilton Jacobi Bellman equations", CEMRACS 2017 - Numerical methods for stochastic models: control, uncertainty quantification, mean-field, ESAIM: Proceedings and Surveys, Volume 65 , p 476 - 497 (2019) hjb_2018_08
• "Some machine learning schemes for high-dimensional nonlinear PDEs", with Côme Huré and Huyên Pham, Mathematics of Computation, 89(324):1547–1579,  2020  BSDE_MachineLearning
• "A power plant valuation under asymmetric risk criterion taking into acount maintenance costs", with Clémence Alasseur, Isaque Pimentel and Emmanuel Gobet, 2019   https://www.fime-lab.org/wp-content/uploads/2019/03/AssymRiskEnergy.pdf
• "Neural networks-based backward scheme for fully nonlinear PDEs" with Maximilien Germain, Huyên Pham,   SN Partial Differ. Equ. Appl. 2, 16 (2021). https://doi.org/10.1007/s42985-020-00062-8 ,FullNonLin-rev2   
• "Numerical resolution of McKean-Vlasov FBSDEs using neuralnetworks", with Maximilien Germain, Joseph Mikael,  2022, Methodology and Computing in Applied Probability,  https://doi.org/10.1007/s11009-022-09946-1 MckeanVlassovFBDSE
• 'Risk management with machine learning based algorithms" , with Simon Fecamp and Joseph Mikael, 2021,  Journal of Computational Finance ,volume 25, number 2 Machine_Learning_for_Hedging_V2
• "Discretization and Machine Learning Approximation of BSDEs with a Constraint on the Gains-Process", with Idris Kharroubi and Thomas Lim, in "Monte Carlo Methods and Applications ", 2021 , https://doi.org/10.1515/mcma-2020-2080.   BSDEConst
• "Fast multivariate empirical cumulative distribution function with connection to kernel density estimation", with Nicolas Langrené,  "Computational Statistics and Data Analysis", vol 162, oct  2021 , Lap
• "Deep backward multistep schemes for nonlinear PDEsand approximation error analysis", with Maximilien Germain and Huyên Pham,  SIAM Journal on Scientific Computing 44.1 (2022), A28–A56,   MultiStepArXiv
• "Incentives, lockdown, and testing: from Thucydides’s analysis to the COVID–19 pandemic", with Emma Hubert, Thibault Mastrolia, Dylan Possamai,  Journal of mathematical biology 84.5 (2022)  NewCovid19_BIOMATH(1)
• "Deep learning for efficient frontier calculation in finance",  Journal of Computational Finance, Vol. 26, No. 1, 2022,   MarkovitzALMIEtCeteraArticleVersionFeb2022JCF
• "Neural networks-based algorithms for stochastic control and PDEs in finance", with Maximilien Germain and Huyên Pham,  in  "Machine Learning for Financial Markets: a guide to contemporary practices, Cambridge University Press, Editors: Agostino Capponi and Charles-Albert Lehalle,Cambridge University Press, 2023   MLfinance_handbook
• "DeepSets and their derivative networks for solving symmetric PDEs", with Maximilien Germain, Mathieu Laurière, and Huyên Pham ,  Journal of Scientific Computing , 91:63, 2022, https://doi.org/10.1007/s10915-022-01796-w DeepSetsSymPDE_JSCjournal
• "Rate of convergence for particles approximation of PDEs in Wasserstein space", with Maximilien Germain and Huyên Pham,  Journal of Applied Probability, 1-17. doi:10.1017/jpr.2021.102, 2022  ConvergencePDEWasserstein_JAP
• "Reservoir optimization and Machine Learning methods", to appear in EURO Journal on Computational Optimization, 2023    StorageAndMachineLearningArxiv
• "A level-set approach to the control of state-constrained McKean-Vlasov equations: application to renewable energy storage and portfolio selection", with Maximilien Germain and Huyên Pham, Numerical Algebra, Control and Optimization, 2023, 13(3&4): 555-582. doi: 10.3934/naco.2022033     MKVconstrainedAIMS2022
• "The GroupMax neural network approximation of convex functions",  IEEE Transactions on Neural Networks and Learning Systems, 2023, convexArxiv
• "Neural networks for first order HJB equations and application to front propagation with obstacle terms" with Olivier Bokanowski and Averil Prost, to appear in Partial Differential Equations and Applications, 2023,   frontNN
• "Mean-field neural networks: learning mappings on Wasserstein space" with Huyên Pham, 2022, LearningDistribution
• "Mean-field neural networks-based algorithms for McKean-Vlasov control problems"  with Huyên Pham, 2022,    MasterEquation
• "Quantile and moment neural networks for learning functionals of  distributions", 2023, Quantile_and_moment_networks