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Haut PDF Numerical Methods and Deep Learning for Stochastic Control Problems and Partial Differential Equations

Haut PDF Numerical Methods and Deep Learning for Stochastic Control Problems and Partial Differential Equations ont été compilés par 123dok FR

Numerical Methods and Deep Learning for Stochastic Control Problems and Partial Differential Equations

Numerical Methods and Deep Learning for Stochastic Control Problems and Partial Differential Equations

... probability) and the computer science (reinforcement learning) communities to propose and compare several algo- rithms based on dynamic programming (DP), and deep neural networks (DNN) ... Voir le document complet

271

Development of geostatistical models using stochastic partial differential equations

Development of geostatistical models using stochastic partial differential equations

... community and not from the probabilist ...in Stochastic Analysis, it has not necessarily been grounded on the need of conveniently fitting a stochastic model to a data-set, nor by the need of ... Voir le document complet

315

Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications

Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications

... (3.1), and provide estimates of the value function at time 0 and state 0 for different values of a coefficient ...transfer learning (also referred to as pre-training in the literature): we ... Voir le document complet

40

Study of numerical methods for partial hedging and switching problems with costs uncertainty

Study of numerical methods for partial hedging and switching problems with costs uncertainty

... Bouveret and Chassagneux [ BBC16 ] studied the Bermudan case and Dumitrescu, Elie, Sabbagh and Zhou [ Dum+17 ] the American ...except for [ BBC16 ]. In fact, the control space of the ... Voir le document complet

195

Conditional Monte Carlo Learning for Diffusions I: main methodology and application to backward stochastic differential equations

Conditional Monte Carlo Learning for Diffusions I: main methodology and application to backward stochastic differential equations

... in numerical methods based on Monte Carlo reached recently their limits in dealing with the curse of dimensionality [ 4 ...] and used with regression in [ 1 , 6 ] and with Multilevel method in ... Voir le document complet

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Certified Reduced Basis Methods for Parametrized Partial Differential Equations

Certified Reduced Basis Methods for Parametrized Partial Differential Equations

... final numerical example, we return to a classic problem, dealing with forced steady heat convection combined with heat conduction in a duct with walls at different temperature and of different ...inlet ... Voir le document complet

121

Accelerated finite elements schemes for parabolic stochastic partial differential equations

Accelerated finite elements schemes for parabolic stochastic partial differential equations

... approximations for Cauchy problems for stochastic parabolic PDEs of the form of equation ...of equations arise in various fields of sciences and engineering, for example ... Voir le document complet

38

Deep Learning and Reinforcement Learning for Inventory Control

Deep Learning and Reinforcement Learning for Inventory Control

... which Stochastic Gradient Gdescent (SGD) and ADAptive Moment estimator (ADAM) are more ...batch methods utilize the entire training sets in order to update the parameters in any iteration with a ... Voir le document complet

69

Linear-quadratic stochastic delayed control and deep learning resolution

Linear-quadratic stochastic delayed control and deep learning resolution

... 4 Deep learning scheme 4.1 A quick reminder of PINNs and Deep Galerkin method for PDEs In order to solve ( ...(PINNs) and Deep Galerkin literatures, see Sirignano ... Voir le document complet

38

An efficient spectral method for the numerical solution to stochastic differential equations

An efficient spectral method for the numerical solution to stochastic differential equations

... Stochastic differential equations, Numerical approximation, Spectral expansion, Stochastic ...Introduction Stochastic differential equations (SDE) driven by a white ... Voir le document complet

27

In-Domain Control of Partial Differential Equations

In-Domain Control of Partial Differential Equations

... flow and roughly simulate the behavior of Navier-Stokes equations ...dynamics and dynamic compensators in the control of nonlinear PDEs with multiple in-domain inputs to produce the desired ... Voir le document complet

135

Development of geostatistical models using Stochastic Partial Differential Equations

Development of geostatistical models using Stochastic Partial Differential Equations

... community and not from the probabilist ...in Stochastic Analysis, it has not necessarily been grounded on the need of conveniently fitting a stochastic model to a data-set, nor by the need of ... Voir le document complet

315

Probabilistic numerical methods for high-dimensional stochastic control and valuation problems on electricity markets

Probabilistic numerical methods for high-dimensional stochastic control and valuation problems on electricity markets

... ) and its partial ...modeling, for both reduced-form models as well as structural models, being able to obtain closed-form formulas for the forward price of electricity is a much sought-after ... Voir le document complet

188

Contribution to the study of efficient iterative methods for the numerical solution of partial differential equations

Contribution to the study of efficient iterative methods for the numerical solution of partial differential equations

... Newton methods or inexact Newton±Krylov methods are probably the most pop- ular examples of FC procedures ...linear and non- linear convergences are considered as quite robust (see ...[5] for ... Voir le document complet

319

Recent developments in spectral stochastic methods for the numerical solution of stochastic partial differential equations

Recent developments in spectral stochastic methods for the numerical solution of stochastic partial differential equations

... these problems in an uncertain context remains a crucial issue in the medium or long ...generic methods, applicable to a wide class of problems and exploiting at best the existing know-how ... Voir le document complet

59

Isogeometric methods for hyperbolic partial differential equations

Isogeometric methods for hyperbolic partial differential equations

... FVM and the FEM. Indeed, discontinuous polynomial functions are used and a numerical flux is defined at the interface between cells to reconstruct the ...of problems. It was first introduced ... Voir le document complet

236

Numerical methods for optimal control problems with biological applications

Numerical methods for optimal control problems with biological applications

... optimal control problems for partial differential equations; the origin dates back to the monograph by ...[80] and several books on infinite dimensional optimal ... Voir le document complet

98

Stochastic control methods for optimal transportation and probabilistic numerical schemes for PDEs

Stochastic control methods for optimal transportation and probabilistic numerical schemes for PDEs

... optimal control problems. In this context, for finite difference method, one can only use the explicit scheme, since the implicit scheme needs to invert too many ...constructed and the ... Voir le document complet

150

Fully nonlinear stochastic partial differential equations: non-smooth equations and applications

Fully nonlinear stochastic partial differential equations: non-smooth equations and applications

... operator and H ( p ) = jpj and for convex initial sets were studied using di erent methods by Yip ...Asymptotic problems in phase transitions We present here an example of an asymptotic ... Voir le document complet

12

Minimum time control problems for non autonomous differential equations

Minimum time control problems for non autonomous differential equations

... Crandall and Lions [13, 12]. These tools also allow to perform the numerical analysis of the approxi- mation ...[3] for theoretical studies. Various numerical methods have been also ... Voir le document complet

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