Stochastic-Processes
My book: Gentle Introduction to Chaotic Dynamical Systems. Includes stochastic dynamical systems and statistical properties of numeration systems in any dimension. (by VincentGranville)
torchsde
Differentiable SDE solvers with GPU support and efficient sensitivity analysis. (by google-research)
| Stochastic-Processes | torchsde | |
|---|---|---|
| 1 | 5 | |
| 30 | 1,483 | |
| - | 2.6% | |
| 6.4 | 4.8 | |
| 12 months ago | 8 months ago | |
| Python | Python | |
| - | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stochastic-Processes
Posts with mentions or reviews of Stochastic-Processes.
We have used some of these posts to build our list of alternatives
and similar projects.
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New Book: Gentle Introduction To Chaotic Dynamical Systems
Authored by Dr. Vincent Granville, 82 pages, published in March 2023. Available on our e-Store exclusively, here. See the table contents or sample chapter on GitHub here. The Python code is also in the same repository.
torchsde
Posts with mentions or reviews of torchsde.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-05.
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Google Research • Differentiable SDE solvers with GPU support and efficient sensitivity analysis in PyTorch. For stochastic differential equations in your deep learning models
Github: https://github.com/google-research/torchsde
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[D] Ideal deep learning library
So not just that paper, but also our follow-up papers on the same topic: Neural SDEs as Infinite-Dimensional GANs Efficient and Accurate Gradients for Neural SDEs are in fact implemented in PyTorch, specifically the torchsde library. (Disclaimer: of which I am a developer.)
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[D] Is there any way for GAN to generate arbitrary length of time series signal?
Code: SDE-GAN example in torchsde.
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[P] Final Year Computer Science Project Suggestions
If you're interested in finance then I'd recommend Neural SDEs: https://arxiv.org/abs/2102.03657 https://arxiv.org/abs/2105.13493 https://github.com/google-research/torchsde/blob/master/examples/sde_gan.py
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Simple & Fast GAN Training [D]
This may or may not fit what you're after.