Popular GitHub Repositories for Multivariate Distributions

Book_5_《统计至简》 | 鸢尾花书：从加减乘除到机器学习；上架！

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/classification/clustering/forecasting/anomaly detection/cleaning on incomplete industrial (irregularly-sampled) multivariate TS with NaN missing values

the open-source virtual assistant for Ubuntu based Linux distributions

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)

PyTorch Dual-Attention LSTM-Autoencoder For Multivariate Time Series

Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

This repository contains a reading list of papers on Time Series Segmentation. This repository is still being continuously improved.

Multivariate LSTM Fully Convolutional Networks for Time Series Classification

The official PyTorch implementation of the paper "SAITS: Self-Attention-based Imputation for Time Series". A fast and state-of-the-art (SOTA) deep-learning neural network model for efficient time-series imputation (impute multivariate incomplete time series containing NaN missing data/values with machine learning). https://arxiv.org/abs/2202.08516

Promotes development of ML algorithms for early detection and classification of undesirable events in offshore oil wells.

Code for our SIGKDD'22 paper Pre-training-Enhanced Spatial-Temporal Graph Neural Network For Multivariate Time Series Forecasting.

Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.

Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

Code & Data for "Tabular Transformers for Modeling Multivariate Time Series" (ICASSP, 2021)

A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python

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

[AAAI2023] A PyTorch implementation of PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction.