Time series forecasting with PyTorch

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backend

Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version

time series forecasting using pytorch，including ANN,RNN,LSTM,GRU and TSR-RNN，experimental code

PyTorch code for Learning Deep Time-index Models for Time Series Forecasting (ICML 2023)

Acquiring data from Alpha Vantage and predicting stock prices with PyTorch's LSTM

PyTorch GPU implementation of the ES-RNN model for time series forecasting

[ICCV 2021] Official PyTorch Implementation of "AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting".

PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

Graph-based weather forecasting models. Originally, PyTorch implementation of Ryan Keisler's 2022 "Forecasting Global Weather with Graph Neural Networks" paper (https://arxiv.org/abs/2202.07575)

Official implement for "SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion"(NeurIPS'24) in PyTorch.

PyTorch implementation of Transformer model used in "Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case"

Official PyTorch implementation of TSDiff models presented in the NeurIPS 2023 paper "Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting"

PyTorch code for CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting (ICLR 2022)

A pip-installable PyTorch implementation of TSMixer, providing an easy-to-use and efficient solution for time-series forecasting.

Paper:Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting . Implementation of spatio-temporal graph convolutional network with PyTorch

Deep learning PyTorch library for time series forecasting

This is an official Pytorch implementation of Conditional Local Convolution for Spatio-temporal Meteorological Forecasting, AAAI 2022

PyTorch implementation of "Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective" (NeurIPS 2024)

Pytorch implementation of NIPS'23 paper: Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective

PyTorch Implementation of "Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting" (AAAI2025)

This is an official PyTorch implementation of the NeurIPS 2023 paper 《OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling》

Using the Pytorch to build an image temporal prediction model of the encoder-forecaster structure, ConvGRU kernel & ConvLSTM kernel

PyTorch Implementation of "TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting" (ICML 2025)

This is the pytorch implementation of Basisformer in the Neurips paper: [BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis]

My personal PyTorch framework for multivariate time series forecasting.

Official implement for "PGN: The RNN’s New Successor is Effective for Long-Range Time Series Forecasting"(NeurIPS 2024) in PyTorch.