Pinned Repositories
aLSI
Asymmetric Latent Semantic Indexing
bayesopt.github.io
BayesOpt
cards-jekyll-template
A simple Jekyll Template Card Based.
differential-privacy-bayesian-optimization
This repo contains the underlying code for all the experiments from the paper: "Automatic Discovery of Privacy-Utility Pareto Fronts"
dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
dpp
Python package to sample from determinantal point processes
emukit
A Python-based toolbox of various methods in uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.
javiergonzalezh.github.io
python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis.
RobustPLS
Matlab package for robust high dimensional regression
javiergonzalezh's Repositories
javiergonzalezh/dpp
Python package to sample from determinantal point processes
javiergonzalezh/RobustPLS
Matlab package for robust high dimensional regression
javiergonzalezh/javiergonzalezh.github.io
javiergonzalezh/python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and sensitivity analysis.
javiergonzalezh/aLSI
Asymmetric Latent Semantic Indexing
javiergonzalezh/bayesopt.github.io
BayesOpt
javiergonzalezh/cards-jekyll-template
A simple Jekyll Template Card Based.
javiergonzalezh/differential-privacy-bayesian-optimization
This repo contains the underlying code for all the experiments from the paper: "Automatic Discovery of Privacy-Utility Pareto Fronts"
javiergonzalezh/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
javiergonzalezh/emukit
A Python-based toolbox of various methods in uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.
javiergonzalezh/gpss15
Gaussian Process Summer School, Sheffield, 2015
javiergonzalezh/hi-ml
Microsoft Health Intelligence Azure Machine Learning Toolbox
javiergonzalezh/incubator-mxnet
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
javiergonzalezh/MXFusion
Modular Probabilistic Programming on MXNet
javiergonzalezh/odest
ODE estimation via RKHS regularization in R
javiergonzalezh/pybo
Python package for modular Bayesian optimization
javiergonzalezh/Spearmint
Spearmint Bayesian optimization codebase
javiergonzalezh/talks
Talks from Neil Lawrence
javiergonzalezh/v108
Proceedings of AISTATS 2020