A code library for reading and preprocessing public battery dataset

Official Code for "CMamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting"

Official implementation for ICML24 paper "Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach"

An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730

Official Implementation of STG-Mamba: Spatial-Temporal Graph Learning via Selective State Space Model.

Mamba or Transformer for Time Series Forecasting? Mixture of Universals (MoU) Is All You Need.

This is the official repository for the paper "Long Input Network for Long Time Series Forecasting"

A Lightweight Framework for Skeleton-Based Gait Recognition with Novel Graph Convolution Network

This is the implementation of our paper entitled "Graph Neural Networks for Multivariate Time-Series Forecasting via Hierarchically Spatiotemporal Dependencies Learning".

Multi-Scale Information Granule-Based Time Series Forecasting Model with Two-Stage Prediction Mechanism

NTU EE3180 Design Innovation Project 3S Battery Management System (BMS) AY2023-24

DIPformer: A Deep Invert Patching Transformer for Battery State of Health Estimation

[ICLR 2024] Official implementation of "TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting"

Code release of paper "MLGN: Multi-Scale Local-Global Feature Learning Network for Long-term Series Forecasting" 💚

Multivariate Time Series Forecasting Model with Graph Neural Networks Incorporating Multi-scale Local and Global Information Fusion

The source code of the model: Multi-Scale Graph Convolutional Network with Contrastive-Learning enhanced Self-attention Pooling (MSGCN-CSP).

This is the repository for paper "MSGNN: Multi-scale Spatio-temporal Graph Neural Network for Epidemic Forecasting", accepted by Data Mining and Knowledge Discovery (DMKD) in 2024.

PyTorch Implementation of "Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting"

A study on volume-price factor stock selection model based on wavelet transform and multitask self-attention network

The code for the paper "[ICLR'24]MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process"

This is official code for paper "Few-Shot Bearing Fault Diagnosis via Ensembling Transformer-based Model with Mahalanobis Distance Metric Learning from Multiscale Features". IEEE Transactions on In…

Multi Task Learning Time Series Momentum

A Dual-View Style Mixing Network for Unsupervised Cross-Domain Fault Diagnosis With Imbalanced Data