Interpolation and function approximation with JAX

Matplotlib styles for scientific plotting

High-performance quantum systems simulation with JAX (GPU-accelerated & differentiable solvers).

Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)

Optimizing matrix-mimetic tensor algebras

Development repository for the Bioconductor package 'mixOmics '

Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.

Learning in infinite dimension with neural operators.

The machine learning toolkit for time series analysis in Python

PyWavelets - Wavelet Transforms in Python

STUMPY is a powerful and scalable Python library for modern time series analysis

Projected tensor-tensor products for multiway data compression

This Python tool helps visualizing statistical significance on existing Matplotlib plots by adding significance bars and p-value labels between chosen pairs of columns.

add statistical significance annotations on seaborn plots. Further development of statannot, with bugfixes, new features, and a different API.

A toolkit for machine learning from time series

Bayesian Change-Point Detection and Time Series Decomposition

Extra blocks for scikit-learn pipelines.

Developer tool for scientific Python libraries

Statistical package in Python based on Pandas

Functional Data Analysis Python package

A framework for composing Neural Processes in Python

`MeTEor` is an R Shiny application that offers the possibility to explore longitudinal metabolomics data. For this purpose, a variety of statistical analysis and visualization methods are implement…

Fast and modular sklearn replacement for generalized linear models

"Probabilistic Machine Learning" - a book series by Kevin Murphy

Matrix-Mimetic Tensor Neural Networks

Dimensionality reduction techniques for order-3 tensors

A hands-on tutorial of deep neural networks for mathematicians

A lightweight, multithreaded Python package for sketching, column selection, leverage scores and related computations.