Use Stan models in JAX for Bayesian inference.

Variational inference with normalizing flows in JAX.

Self-tuning HMC algorithms and evaluations

PyTorch implementation of normalizing flow models

Reimplementation using Python of the minimax tilting algorithm by Botev (2016) for simulation and iid sampling of the truncated multivariate normal distribution.

STATS320: Statistical Methods for Neural Data Analysis

Monte Carlo with determinantal point processes

EB1A Full Application - I-140 and I-485

R Software for inference using multicarving

Samplin' Safari is a research tool to visualize and interactively inspect high-dimensional (quasi) Monte Carlo samplers.

Python library for shrinkage cleaning of large correlation matrices.

Variational Bayesian skyline infers evolutionary models from large amounts of phylogenetic data.

A package for shrinkage estimation of covariance matrices

A Package for Shrinkage Estimation of Covariance Matrices

A package for Shrinkage Estimation of Covariance Matrices

健康学习到150岁 - 人体系统调优不完全指南

Implementation contained in "Demystifying Orthogonal Monte Carlo and Beyond"

Guided Evolutionary Strategies

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

A Python toolbox for performing gradient-free optimization

Code for "Policy Learning and Evaluation with Randomized Quasi-Monte Carlo"

Code to run the ASEBO algorithm from the paper: From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization... please get in touch if interested!!

Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.

Safari extension to save your working sessions

A Type-1 Diabetes simulator implemented in Python for Reinforcement Learning purpose

List of CGM datasets

PyTorch implementation of Contrastive Learning methods