TimEgan

Dual-dimension Time-GGAN data augmentation method for improving the performance of deep learning models for PV power forecasting - ScienceDirect

Modeling and Generating Time-Series Data using TimeGAN, by Archit Yadav

阅读笔记Time-series Generative Adversarial Networks - 知乎

machine-learning-for-trading/21_gans_for_synthetic_time_series/README.md at main · stefan-jansen/machine-learning-for-trading · GitHub

Sustainability, Free Full-Text

Dodsworth In New York - (dodsworth Book) By Tim Egan (paperback) : Target

A Conditional Generative adversarial Network for energy use in multiple buildings using scarce data - ScienceDirect

GitHub - birdx0810/timegan-pytorch: This repository is a non-official implementation of TimeGAN (Yoon et al., NIPS2019) using PyTorch.

TimeGAN: A Novel Solution to Imbalanced Encrypted Traffic Datasets

Machine intelligent Forex Trading Using ForeX-TimeGANs

How a pilgrimage reignited Tim Egan's faith

TimeGAN Archives - QUANTITATIVE RESEARCH AND TRADING

Training the TimeGAN model to generate data.

The best Generative AI Model for Time-Series Synthetic Data Generation