Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Download market data from Yahoo! Finance's API

JAX - A curated list of resources https://github.com/google/jax

Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

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

Control with Deep Reinforcement Learning

Bayesian inference and posterior analysis for Python

Code for our paper "Hamiltonian Neural Networks"

High-Performance Symbolic Regression in Python and Julia

Gaussian processes framework in python

Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations

Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"

Couplings for nonlinear ensemble filtering

The Python Control Systems Library is a Python module that implements basic operations for analysis and design of feedback control systems.

Companion Matlab and Python codes for the book Bayesian Filtering and Smoothing by Simo Särkkä and Lennart Svensson

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

code for the paper: Consistency of Empirical Bayes And Kernel Flow For Hierarchical Parameter Estimation

Gaussian Processes regression and classification implementations, as well as notebook for accompanying blog. Blog static site:

Sequential Monte Carlo in python

Some Monte Carlo algorithms for the estimation of small probabilities associated with rare events

Análisis estructural por elementos finitos