Stars
A Library for Advanced Deep Time Series Models.
The Electricity Transformer dataset is collected to support the further investigation on the long sequence forecasting problem.
Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight), https://openreview.net/forum?id=JePfAI8fah
Deep Residual Learning in Spiking Neural Networks
Spikingformer: Spike-driven Residual Learning for Transformer-based Spiking Neural Network
A project for solving demand forecast of a medium retailer using a simple Deep Learning model
A time series forecasting project from Kaggle that uses Seq2Seq + LSTM technique to forecast the headcounts. Detailed explanation on how the special neural network structure works is provided.
Learning materials, files and codes for bioinformatics
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
This is a python package for genomics study with a GCN framework.
Lightning ⚡️ fast forecasting with statistical and econometric models.
This is a repository for Multi-task learning with toy data in Pytorch and Tensorflow
Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting
Example usage of scikit-hts
[CIKM 2023] This is the official source code of "TrendGCN: Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic Forecasting" based on Pytorch.
code of DeepGWC: A Deep Graph Wavelet Convolutional Neural Network for Semi-supervised Node Classification
Probabilistic time series modeling in Python
A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
Implementation of the paper NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series Forecasting.
A PyTorch implementation of the Transformer model in "Attention is All You Need".