A sample code of data augmentation methods for wearable sensor data (time-series data)

Data augmentation using synthetic data for time series classification with deep residual networks

TTS-CGAN: A Transformer Time-Series Conditional GAN for Biosignal Data Augmentation

TensorFlow in Practice Specialization. Join our Deep Learning Adventures community 🎉 and become an expert in Deep Learning, TensorFlow, Computer Vision, Convolutional Neural Networks, Kaggle Challenges, Data Augmentation and Dropouts Transfer Learning, Multiclass Classifications and Overfitting and Natural Language Processing NLP as well as Time Series Forecasting 😀 All while having fun learning and participating in our Deep Learning Trivia games 🎉 http://bit.ly/deep-learning-tf

AugmentTS :: Time Series Data Augmentation using Deep Generative Models

The repository provides code implementations and illustrative examples of NeurIPS 2023 paper, Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning.

Official code for "SimPSI: A Simple Strategy to Preserve Spectral Information in Time Series Data Augmentation", AAAI 2024.

Data augmentation for multivariate time series classification

This repository contains all the source code needed to reproduce the experiments or review the results obtained in the research paper "D3A-TS: Denoising-Driven Data Augmentation in Time Series"

WWGAN (Worm Wasserstein GAN), a Generative Adversarial Network (GAN) for time-series data augmentation

This is the implementation for the paper "Empirical Evaluation of Data Augmentations for Biobehavioral Time Series Data with Deep Learning"

Deep Learning Adventures. Join our Deep Learning Adventures community 🎉 and become an expert in Deep Learning, TensorFlow, Computer Vision, Convolutional Neural Networks, Kaggle Challenges, Data Augmentation and Dropouts Transfer Learning, Multiclass Classifications and Overfitting and Natural Language Processing NLP as well as Time Series Forecasting 😀 All while having fun learning and participating in our Deep Learning Trivia games 🎉 http://bit.ly/deep-learning-tf

ICPR2022: Dynamic Data Augmentation with Gating Networks for Time Series Recognition

Data augmentation using synthetic data for time series classification with deep residual networks

Time Series Data Augmentation on Seismic Data

🌟Learning Hierarchical Time Series Data Augmentation Invariances via Contrastive Supervision for Human Activity Recognition

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Rapid Augmentation Library for Time Series data

Time Series Domain Data Augmentation

Data augmentation for time series classification

Self-Supervised Time-Series Anomaly Detection using Learnable Data Augmentation

Improving Neural Networks for Time-Series Forecasting using Data Augmentation and AutoML

An official implementation of DiffAT: Effective data augmentation with diffusion models for time series forecasting

SigVarGen is a Python framework for time-series signal generation, data augmentation, and anomaly simulation. It creates diverse 1D signal variants under controlled conditions, including idle-state, perturbed, and noisy signals.

A repository for time series data augmentation including population based augmentation.

Time Series Augmentation: In-depth analysis with Biomedical Data

Deep Learning Methods for Time Series Data Mining (Time series Classification, Augmentation, TimeGAN...) implemented by torch

Improving Solar Energetic Particle Event Prediction through Multivariate Time Series Data Augmentation

Data Augmentation for Multivariate Time Series