Probabilistic Forecasting Python 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

calibrax

JAX benchmarking, profiling and evaluation metrics for Flax NNX: a registry of pure-function metrics (regression, classification, calibration, uncertainty, forecasting, generative, image, text, audio, graph, fairness), XLA FLOP counting, roofline analysis, GPU and energy monitoring, regression detection, publication exports, W&B and MLflow.

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

fracast

Fracast-0 is an 85K-parameter pretrained Time Series Foundation Model, small enough to load directly in a web page.

ondil

A package for online distributional learning.

rolch

A package for online distributional learning.

kernel-quantile-regression

Kernel quantile regression

base-attentive

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

reservoir-computing

Implement Reservoir Computing models for time series classification, clustering, forecasting, and much more!

pyfts

An open source library for Fuzzy Time Series in Python

stengression

Spatiotemporal engression for probabilistic forecasting on low-frequency datasets.