Pinned Repositories
ASTGCN
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN) AAAI 2019
ASTGCN-r-pytorch
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version
ASTGNN
This is a Pytorch implementation of ASTGNN. Now the corresponding paper is available online at https://ieeexplore.ieee.org/document/9346058.
BasicTS
An Open Source Standard Time Series Forecasting Benchmark.
Clustering-based_Data_Analysis
This repo contains notebook of the Python code for performing clustering of turbines in a wind farm
energy-forecast
The repository consists of an energy forecasting model using XGboost. The dataset consists of hourly energy consumption rates in kWh for an industrial utility.
GNNPapers
Must-read papers on graph neural networks (GNN)
mlforecast
Scalable machine š¤ learning for time series forecasting.
MSDR
Implementation for MSDR
PaddleTS
Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supporting versatile tasks like time series forecasting, representation learning, and anomaly detection, etc., featured with quick tracking of SOTA deep models.
zmhhh578's Repositories
zmhhh578/ASTGCN
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN) AAAI 2019
zmhhh578/ASTGCN-r-pytorch
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version
zmhhh578/ASTGNN
This is a Pytorch implementation of ASTGNN. Now the corresponding paper is available online at https://ieeexplore.ieee.org/document/9346058.
zmhhh578/BasicTS
An Open Source Standard Time Series Forecasting Benchmark.
zmhhh578/Clustering-based_Data_Analysis
This repo contains notebook of the Python code for performing clustering of turbines in a wind farm
zmhhh578/energy-forecast
The repository consists of an energy forecasting model using XGboost. The dataset consists of hourly energy consumption rates in kWh for an industrial utility.
zmhhh578/GNNPapers
Must-read papers on graph neural networks (GNN)
zmhhh578/mlforecast
Scalable machine š¤ learning for time series forecasting.
zmhhh578/MSDR
Implementation for MSDR
zmhhh578/PaddleTS
Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supporting versatile tasks like time series forecasting, representation learning, and anomaly detection, etc., featured with quick tracking of SOTA deep models.
zmhhh578/Pollution-Prediction-GNN
A repository for making models based on GNN to predict pollution levels in megacity delhi. The input is a partial data in time and space which is used along with other regional features of a location to predict pollution levels of the centres which are unrecorded.
zmhhh578/Pyraformer
zmhhh578/pytorch-forecasting
Time series forecasting with PyTorch
zmhhh578/pytorch_geometric_temporal
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
zmhhh578/StemGNN
Spectral Temporal Graph Neural Network (StemGNN in short) for Multivariate Time-series Forecasting
zmhhh578/STGNN
The pytorch implementation of Traffic Flow Prediction via Spatial Temporal Graph Neural Network
zmhhh578/STSGT
Spatial-Temporal Synchronous Graph Transformer network (STSGT) for COVID-19 forecasting
zmhhh578/Time-Series-Library
A Library for Advanced Deep Time Series Models.
zmhhh578/Transformer_Time_Series
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting (NeurIPS 2019)
zmhhh578/TSAT
Transformer based model for time series prediction
zmhhh578/TSF-AirPollution
Multivariate Multi-Step Time Series Forecasting Models for Air Pollution.
zmhhh578/TSF_LSTF_Compare
Time series forecasting especially in LSTF compareļ¼include Informer, Autoformer, Reformer, Pyraformer, FEDformer, Transformer, MTGNN, LSTNet, Graph WaveNet
zmhhh578/wind-energy-analytics
Physics-guided data-driven solutions for the wind energy industry
zmhhh578/xunfei