Alternatives and similar repositories for DeepBSDE-pytorch

Users that are interested in DeepBSDE-pytorch are comparing it to the libraries listed below

• ZichaoLong / PDE-Net
  PDE-Net: Learning PDEs from Data
  ☆327Updated 4 years ago
• ZichaoLong / aTEAM
  A pyTorch Extension for Applied Mathematics
  ☆40Updated 5 years ago
• maziarraissi / FBSNNs
  Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations
  ☆155Updated 5 years ago
• frankhan91 / DeepBSDE
  Deep BSDE solver in TensorFlow
  ☆287Updated 8 months ago
• sisl / deep_flow_control
  Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018
  ☆49Updated 7 years ago
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆91Updated 3 years ago
• maziarraissi / DeepHPMs
  Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
  ☆283Updated 3 years ago
• alialaradi / DeepGalerkinMethod
  Companion code for "Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning" by A. Al-Aradi, A. Correia, …
  ☆122Updated 6 years ago
• batuhanguler / Deep-BSDE-Solver
  Solving high-dimensional Partial Differential Equations with Deep Learning
  ☆27Updated 6 years ago
• lorenzrichter / PDE-backward-solver
  ☆22Updated last year
• n-takeishi / learning-kis
  Demo implementation of Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition
  ☆40Updated 3 years ago
• bhushan23 / ADMM
  Implemented ADMM for solving convex optimization problems such as Lasso, Ridge regression
  ☆157Updated 4 years ago
• cics-nd / cnn-surrogate
  Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
  ☆107Updated 5 years ago
• Physics-aware-AI / Symplectic-ODENet
  ☆46Updated 5 years ago
• ELIFE-ASU / INNLab
  A python/pytorch package for invertible neural networks
  ☆70Updated 2 years ago
• ORNL / AADL
  Anderson Acceleration for Deep Learning
  ☆13Updated 3 years ago
• 2prime / LM-ResNet
  Code For Beyond Finite Layer Neural Network:Bridging Deep Architects and Numerical Differential Equations
  ☆15Updated 6 years ago
• scaomath / galerkin-transformer
  [NeurIPS 2021] Galerkin Transformer: a linear attention without softmax for Partial Differential Equations
  ☆254Updated last year
• Rachnog / Neural-ODE-Experiments
  This repository contains experiments with Neural Ordinary Differential Equations with simulated and real empirical data
  ☆199Updated 6 years ago
• LeungSamWai / Finite-expression-method
  ☆20Updated 2 months ago
• Typal-Research / jacobian_free_backprop
  Implicit networks can be trained efficiently and simply by using Jacobian-free Backprop (JFB).
  ☆41Updated 4 years ago
• xuzhiqin1990 / F-Principle
  code to show F-Principle in the DNN training
  ☆59Updated 3 years ago
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆26Updated 6 years ago
• pooyasf / DGM
  Solving High Dimensional Partial Differential Equations with Deep Neural Networks
  ☆34Updated 3 years ago
• massastrello / awesome-implicit-neural-models
  ☆105Updated 4 years ago
• huangleiBuaa / ONI
  PyTorch and Torch implementation for our accepted CVPR 2020 paper (Oral): Controllable Orthogonalization in Training DNNs
  ☆25Updated 4 years ago
• mbudisic / koopman
  Koopman Mode Decomposition
  ☆74Updated 8 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆42Updated 4 years ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆453Updated last year
• ermongroup / sparse_gen
  Code for "Modeling Sparse Deviations for Compressed Sensing using Generative Models", ICML 2018
  ☆24Updated 7 years ago