Search Packages

neuralforecast

Scalable and user friendly neural :brain: forecasting algorithms.

skforecast

Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models

base-attentive

Modular Multi-Backend Encoder-Decoder Architecture for Probabilistic Time Series Forecasting

lightgbmlss

An extension of LightGBM to probabilistic modelling

apdtflow

APDTFlow is a modern and extensible forecasting framework for time series data that leverages advanced techniques including neural ordinary differential equations (Neural ODEs), transformer-based components, and probabilistic modeling. Its modular design allows researchers and practitioners to experiment with multiple forecasting models and easily

kernel-quantile-regression

Kernel quantile regression

ondil

A package for online distributional learning.

rolch

A package for online distributional learning.

reservoir-computing

Library for implementing reservoir computing models (Echo State Networks) for multivariate time series classification, clustering, and forecasting.

pyfts

Fuzzy Time Series for Python

stengression

Deep spatiotemporal engression networks for probabilistic forecasting