Multivariate LSTM Fully Convolutional Networks for Time Series Classification

Flexible time series feature extraction & processing

A Full-Pipeline Automated Time Series (AutoTS) Analysis Toolkit.

A meta-analysis package for R

Python toolbox for analyzing imaging data

Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.

Yet another vine copula package, using PyTorch.

Python library for multivariate dependence modeling with Copulas

pyMCR: Multivariate Curve Resolution for Python

🧬High-performance genetics- and genomics-related data visualization using Makie.jl

Scikit-Learn compatible HMM and DTW based sequence machine learning algorithms in Python.

Time-Series models for multivariate and multistep forecasting, regression, and classification

Multivariate Local Polynomial Regression and Radial Basis Function Regression

Multivariate Regression and Classification Using an Adaptive Neuro-Fuzzy Inference System (Takagi-Sugeno) and Particle Swarm Optimization.

Fast and differentiable geometric median, a multivariate median analogue. Install with `pip install geom-median`

An Android library for generating simple A/B tests

Financial Time Series Price forecast using Keras for Tensorflow. RNN LSTM

Julia package containing utilities intended for Time Series analysis.

This is the implementation of the paper Enhanced Photovoltaic Power Forecasting: An iTransformer and LSTM-Based Model Integrating Temporal and Covariate Interactions

Implementation of the Random Dilated Shapelet Transform algorithm along with interpretability tools. ReadTheDocs documentation is not up to date with the current version for now.