This is the Windows app named PyTorch Implementation of SDE Solvers whose latest release can be downloaded as v0.2.6.zip. It can be run online in the free hosting provider OnWorks for workstations.
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PyTorch Implementation of SDE Solvers
DESCRIPTION
This library provides stochastic differential equation (SDE) solvers with GPU support and efficient backpropagation. examples/demo.ipynb gives a short guide on how to solve SDEs, including subtle points such as fixing the randomness in the solver and the choice of noise types. examples/latent_sde.py learns a latent stochastic differential equation, as in Section 5 of [1]. The example fits an SDE to data, whilst regularizing it to be like an Ornstein-Uhlenbeck prior process. The model can be loosely viewed as a variational autoencoder with its prior and approximate posterior being SDEs. The program outputs figures to the path specified by
Features
- Requirements: Python >=3.6 and PyTorch >=1.6.0
- Neural SDEs as GANs
- Latent SDE
- GPU support and efficient backpropagation
- Stochastic differential equation (SDE) solvers
- Several keyword arguments are also accepted
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/pytorch-imp-sde-solvers.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
