Alternatives and similar repositories for Deep-BSDE-Solver

Users that are interested in Deep-BSDE-Solver are comparing it to the libraries listed below

• frankhan91 / DeepBSDE
  Deep BSDE solver in TensorFlow
  ☆279Updated 4 months ago
• maziarraissi / FBSNNs
  Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations
  ☆155Updated 5 years ago
• pooyasf / DGM
  Solving High Dimensional Partial Differential Equations with Deep Neural Networks
  ☆34Updated 3 years ago
• msabvid / robust_nsde
  Robust pricing and hedging via Neural SDEs
  ☆37Updated 4 years ago
• alialaradi / DeepGalerkinMethod
  Companion code for "Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning" by A. Al-Aradi, A. Correia, …
  ☆118Updated 6 years ago
• jkirkby3 / pymle
  Maximum Likelihood estimation and Simulation for Stochastic Differential Equations (Diffusions)
  ☆54Updated 3 weeks ago
• tonyshardlow / PICSPDE
  Python codes for Introduction to Computational Stochastic PDE
  ☆44Updated 6 months ago
• msabvid / Deep-PDE-Solvers
  Unbiased Deep Learning based Solvers for parametric PDEs
  ☆11Updated 3 years ago
• MaxGermain / MultistepBSDE
  Deep multistep methods to solve BSDEs of first and second order for the approximation of PDE solutions
  ☆19Updated 5 years ago
• justinhou95 / NeuralHedge
  Pytorch implementation of Deep Hedging, Utility Maximization and Portfolio Optimization
  ☆15Updated 11 months ago
• sdepy / sdepy
  SdePy: Numerical Integration of Ito Stochastic Differential Equations
  ☆43Updated 4 years ago
• vicaws / neuralSDE-marketmodel
  Python modules and jupyter notebook examples for the paper Arbitrage-free Neural-SDE Market Models.
  ☆52Updated 2 years ago
• Bayes-Works / OpenBDLM
  Bayesian Dynamic Linear Models for time-series analysis
  ☆27Updated 3 years ago
• janblechschmidt / PDEsByNNs
  This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…
  ☆176Updated 4 years ago
• helange23 / from_fourier_to_koopman
  Linear and non-linear spectral forecasting algorithms
  ☆137Updated 4 years ago
• msabvid / Deep-PPDE
  Deep Learning methods to solve path-dependent PDEs / to price path-dependent derivatives like exotic options
  ☆35Updated 3 years ago
• snagcliffs / RKNN
  ☆20Updated 7 years ago
• oskarimikkila / Empirical-Deep-Hedging
  ☆16Updated 3 years ago
• anfelopera / lineqGPR
  Gaussian processes regression models with linear inequality constraints
  ☆15Updated last year
• 732jhy / Fractional-Brownian-Motion
  Python implementation of fractional brownian motion
  ☆62Updated 5 years ago
• LRydin / jumpdiff
  JumpDiff: Non-parametric estimator for Jump-diffusion processes for Python
  ☆48Updated 2 years ago
• SigCGANs / Sig-Wasserstein-GANs
  ☆27Updated 2 years ago
• erichson / koopmanAE
  Consistent Koopman Autoencoders
  ☆74Updated 2 years ago
• amuguruza / RoughFCLT
  ☆19Updated 7 years ago
• AlessandroGnoatto / DeepBsdeSolverWithJumps
  Implementation of "A deep solver for BSDEs with jumps"
  ☆14Updated 9 months ago
• janiechen8 / DeepLSMethod
  ☆10Updated 4 years ago
• chrischia06 / neural-network-derivative-pricing
  Survey of neural network methods for derivatives pricing and risks
  ☆14Updated 3 years ago
• HeKrRuTe / OptStopRandNN
  code for "Optimal Stopping via Randomized Neural Networks"
  ☆58Updated last year
• pafoster / path_signatures_introduction
  A Brief Introduction to Path Signatures for Machine Learning Practitioners
  ☆53Updated 4 years ago
• yangangchen / Amer_Op_Neural_Net
  Deep Neural Network Framework Based on Backward Stochastic Differential Equations for Pricing and Hedging American Options in High Dimens…
  ☆21Updated 4 years ago