SolarCloud: Forecasting Photovoltaic Production

PyTorch implementation of "Conditional Image Generation with PixelCNN Decoders" by van den Oord et al. 2016

This repository contains several smaller projects and tutorials that I've created for fun about time series analysis in R.

Tutorial on VAR models + regularization

List of papers and code for relevant Generative Models

Auto Regressive Models applied on Paris Subway Stations. Time Series Analysis. Predictions of affluence.

Forecasting Monthly Sales of French Champagne - Perrin Freres

Implementing Bayes by Backprop with PyTorch. Applied on time-series prediction.

Pytorch implementations of autoregressive pixel models - PixelCNN, PixelCNN++, PixelSNAIL

Proof of concept for online hybrid message passing inference for AR-HGF.

Abstract: The S&P500 is difficult to predict. Multi-factor models provide a useful framework for making returns predictions and for controlling portfolio risk. This paper explores a three-step process in predicting PCA and Autoencoders factors to generate multi-factor models from the S&P500 component securities.

A tutorial to time-series analysis techniques. Holt-Winter methods, ACF/PACF, MA, AR, ARMA, ARIMA, SARIMA, SARIMAX, VAR, VARMA etc.

Statistical Learning Models for Damage Detection in Civil Structures.

Implementation of the genetic algorithm for structural break detection in time series that chooses a piecewise autoregressive model using minimum description length principle

Need to predict how many passengers are going to opt for the airline base on the historical information provided by the Airlines. Using various Time series techniques predicted the number of passengers

A Repo of Time-series analysis techniques. Holt-Winter methods, ACF/PACF, MA, AR, ARMA, ARIMA, SARIMA, SARIMAX, VAR, VARMA, RNN Keras, Facebook- Prophet etc.

Implementation for Some Deep Generative Models

Statistics and Forecasting for the Coronavirus disease (COVID-19) in the European Union