ynning

External-Attention-pytorch

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

PyTorch-Tutorial

Build your neural network easy and fast, 莫烦Python中文教学

Time-Series-Library

A Library for Advanced Deep Time Series Models.

deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting

time-series-transformers-review

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

LTSF-Linear

[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

ConvLSTM_pytorch

Implementation of Convolutional LSTM in PyTorch.

PatchTST

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

iTransformer

Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight), https://openreview.net/forum?id=JePfAI8fah

Seq2Seq-PyTorch

Sequence to Sequence Models with PyTorch

seq2seq

Minimal Seq2Seq model with Attention for Neural Machine Translation in PyTorch

Deep-Time-Series-Prediction

Seq2Seq, Bert, Transformer, WaveNet for time series prediction.

Nonstationary_Transformers

Code release for "Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting" (NeurIPS 2022), https://arxiv.org/abs/2205.14415

encoder_decoder

Four styles of encoder decoder model by Python, Theano, Keras and Seq2Seq

CNN-LSTM-Attention

使用卷积神经网络-长短期记忆网络（bi-LSTM）-注意力机制对股票收盘价进行回归预测。The convolution neural network, short-term memory network and attention mechanism are used to predict the closing price.

LSTM-Load-Forecasting

Implementation of Electric Load Forecasting Based on LSTM(BiLSTM). Including Univariate-SingleStep forecasting, Multivariate-SingleStep forecasting and Multivariate-MultiStep forecasting.

PatchMixer

About Code release for "PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting"

AST

Adversarial Sparse Transformer for Time Series Forecasting

DeepRNN

long-term blood pressure prediction with deep recurrent neural networks

SegRNN

The official repository of the SegRNN paper: "Segment Recurrent Neural Network for Long-Term Time Series Forecasting." This work is developed by the Lab of Professor Weiwei Lin (linww@scut.edu.cn), South China University of Technology; Pengcheng Laboratory.

Dish-TS

Time Series Forecasting, Distribution Shift

massformer

Tandem Mass Spectrum Prediction with Graph Transformers

KDDCUP2022

[KDD CUP 2022] 11th place solution of Spatial-Temporal Graph Neural Network for Wind Power Forecasting in Baidu KDD CUP 2022

triformer

api-examples

API examples to retrieve spectrum data from electrosense

MTPNet

LTSF-linear-API

API for LSTF-Linear, SOTA for time-series-forecasting.

EnhanceNet

Major-Project

Machine Learning algorithms for Spectrum sensing

FMTCN4LTSF

The code of "A novel approach for long-term time series forecasting: Frequency-domain enhanced multi-scale temporal convolutional network with a hybrid loss function"