stochastica
torchsde
| stochastica | torchsde | |
|---|---|---|
| 1 | 5 | |
| 4 | 1,481 | |
| - | 2.5% | |
| 0.0 | 4.8 | |
| about 2 years ago | 7 months ago | |
| HTML | Python | |
| MIT License | Apache License 2.0 |
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stochastica
torchsde
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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.
What are some alternatives?
torchdyn - A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
pysindy - A package for the sparse identification of nonlinear dynamical systems from data
tabnet - PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf
SSD-pytorch - SSD: Single Shot MultiBox Detector pytorch implementation focusing on simplicity
NeuralCDE - Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)
functorch - functorch is JAX-like composable function transforms for PyTorch.
pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs
hasktorch - Tensors and neural networks in Haskell
tsalib - Tensor Shape Annotation Library (numpy, tensorflow, pytorch, ...)
dex-lang - Research language for array processing in the Haskell/ML family
DifferentialEquations.jl - Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
torchtyping - Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.