List of papers, code and experiments using deep learning for time series forecasting
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
Time series analysis in the `tidyverse`
AtsPy: Automated Time Series Models in Python (by @firmai)
Streamlit app to train, evaluate and optimize a Prophet forecasting model.
An open source library for Fuzzy Time Series in Python
Graph-based weather forecasting models. Originally, PyTorch implementation of Ryan Keisler's 2022 "Forecasting Global Weather with Graph Neural Networks" paper (https://arxiv.org/abs/2202.07575)
PyTorch implementation of Transformer model used in "Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case"
QGIS toolkit 🧰 for pre- and post-processing 🔨, visualizing 🔍, and running simulations 💻 in the Weather Research and Forecasting (WRF) model 🌀
Extending broom for time series forecasting
The official code for "TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)". TEMPO is one of the very first open source Time Series Foundation Models for forecasting task v1.0 version.
Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.
MSGARCH R Package
Jupyter Notebooks Collection for Learning Time Series Models
Sky Cast: A Comparison of Modern Techniques for Forecasting Time Series
This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to generate a dynamic forecast from your own data.
This repository contains several exercises in Python and R, mainly in the area of finance, financial modeling, and statistics.
Python based Quant Finance Models, Tools and Algorithmic Decision Making
Automatic forecasting and Bayesian modeling for time series with Stan
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