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

A library for Partially Homomorphic Encryption in Python

NeurIPS 2023: Safe Policy Optimization: A benchmark repository for safe reinforcement learning algorithms

3rd Place Solution of KDD Cup 2022-Spatial Dynamic Wind Power Forecasting

KDD Cup 2022 spatial dynamic wind power forecast challenge solution.

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

Wind Power Forecasting Based on Hybrid CEEMDAN-EWT Deep Learning Method

Code for Deep Spatio Temporal Wind Power Forecasting

wind_power_forecast

A combined LSTM and LightGBM framework for improving deterministic and probabilistic wind energy forecasting

Wind Power Forecasting using Machine Learning techniques.

KDDCUP2022 Spatial Dynamic Wind Power Forecasting Paddle Track Sixth Place Solution

This project implements a bagging based spatio-temporal regression model for wind power forecasting.

Adaptive Data Analysis Applied to Wind Power Forecasting

LSTM model for forecasting wind-power generation

Forecast wind power and electricity production of wind turbines

The code of the base model (TCN-GRU) in article "Wind power forecasting: A temporal domain generalization approach incorporating hybrid model and adversarial relationship-based training"

An early prototype of a time-series forecasting app predicting wind power production

LSTM-EFG for wind power forecasting based on sequential correlation features

this is the official pytorch implementation for the paper: 2DXformer: Dual Transformers for Wind Power Forecasting with Dual Exogenous Variables.

Code for "Nonparametric Probabilistic Forecasting for Wind Power Generation using Quadratic Spline Quantile Function and Autoregressive Recurrent Neural Network"

Forecasting Offshore wind Reductions in Cost of Energy

This repository contains the Python implementation of AutoWP for automated wind power forecasts with limited computing resources using an ensemble of diverse wind power curves.

Using AI and ML to predict electricity generation from renewable energies (wind photovoltaics) based on weather data.

KDD Cup 2022 spatial dynamic wind power forecast challenge GRU and RNN ensemble <<Zealen>>

2022 KDD Cup Spatial Dynamic Wind Power Forecast

Ultra-Short-term power forecast method for wind farm based on feature selection and temporal convolution network

The code for paper "Probabilistic Forecasting for Wind Power Generation via Enhanced Conditional Variational Autoencoder with Normalization Flow"