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For beginner, this will be the best start for VAEs, GANs, and CVAE-GAN. This contains AE, DAE, VAE, GAN, CGAN, DCGAN, WGAN, WGAN-GP, VAE-GAN, CVAE-GAN. All use PyTorch.
A library to model multivariate data using copulas.
PyTorch implementations of Generative Adversarial Networks.
Conditional Wasserstein GAN for synthetic time series genetaion
this is the pytorch version of Conditional Generative Adversarial Nets
Implementation of Conditional Generative Adversarial Networks in PyTorch
GANs for Conditional Sequence Generation. Tensorflow. Including the code of paper "Improving Conditional Sequence Generative Adversarial Networks by Stepwise Evaluation" IEEE/ACM TASLP, 2019.
Conditional GAN for generating synthetic tabular data.
Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset
TensorFlow implementation of TimeGAN model for synthetic time series generation with generative adversarial networks.
A survey and paper list of current Diffusion Model for Time Series and SpatioTemporal Data with awesome resources (paper, application, review, survey, etc.).
Official PyTorch implementation of TSDiff models presented in the NeurIPS 2023 paper "Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting"
MTSS-GAN: Multivariate Time Series Simulation with Generative Adversarial Networks (by @firmai)
Thesis project done on Generation Financial Time-Series with GANs. The project was a collaboration between Wholesale Banking Advanced Analytics team with ING and University Maastricht.
A model to generate time series data with the purpose of augmenting a dataset of various time series.
Synthetic data generators for tabular and time-series data
A tensorflow implementation of GAN ( exactly InfoGAN or Info GAN ) to one dimensional ( 1D ) time series data.
Renewable energy scenario generation
Implementation of Deep Temporal Clustering.
📈 Keras implementation of the Deep Temporal Clustering (DTC) model
《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新，English version ongoing
Code for Deep Spatio Temporal Wind Power Forecasting