NeuralProphet: A simple forecasting package

[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

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

This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to generate a dynamic forecast from your own data.

An adaptive model for prediction of one day ahead foreign currency exchange rates using machine learning algorithms

Time series forecast using deep learning transformers (simple, XL, compressive). Implementation in Pytorch and Pytorch Lightning.

Forecast of the level of pollution in the next hour in Beijing based on historical information

Novel algorithms to predict Remaining Useful Life (RUL) on NASA’s benchmark dataset, CMAPSS turbofan engine degradation simulation.

Prediction of material microstructure evolution via convolutional LSTM neural networks. Implementation in pytorch.

Python scripts from CryosphereComputing

Forecast of next month's number of car sales based on historical information

LSTM forecaster showcasing stateful LSTM

A replication in Python and PyRenew of a renewal model written in Epidemia for forecasting influenza hospital admissions.

Regression models mapping m inputs to n outputs. I have tried to make this code as configurable as possible by using .yaml configurations. Please read the config comments and set appropriate config variables to successfully run the application. Also, documentation is generated using Sphinx 1.8.0 and can be read at 'docs_build\html\index.html' in…

A Novel Hybridized Forecasting Technique Utilizing ARIMA and Large Language Models

A complete time series analysis project using Python and ARIMA models for stock price forecasting.

Python code to analyse PV production and weather Data to forecast future production. MSc Thesis.

The Forecast Brazilian Salary API is a powerful tool that allows users to predict salaries based on various factors and parameters.

Manuscript, source codes and data sets on estimating Singapore’s lower-bound SARS-CoV-2 Infection Trend In 2020.