Stars
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
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
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
PyTorch implementation of Contrastive Learning methods