Carmen Sánchez Gil's repositories
SEIDEA
Code and data to solve Interval DEA problems
fabada
Fully Adaptive Bayesian Algorithm for Data Analysis (FABADA) is a new approach of noise reduction methods. In this repository is shown the package developed for this new method based on \citepaper.
cvxpy
A Python-embedded modeling language for convex optimization problems.
dccp
A CVXPY extension for convex-concave programming
somachine2021
SOMACHINE 2021. Machine Learning, Big Data, and Deep Learning in Astronomy. A Severo Ochoa School of the Instituto de Astrofísica de Andalucía (CSIC)
Kalkayotl
This repository contains a code to infer distances to stellar clusters and its stars from Gaia parallaxes.
nnest
Neural network nested and MCMC sampling
notebooks
Tutorial notebooks for Stingray
IAA_School2019
The 1st IAA-CSIC Severo Ochoa School on Statistics, Data Mining and Machine Learning
SPSAS2019
Lectures on "Big Data Sets in Astronomy" by Zeljko Ivezic at Sao Paulo School of Advanced Science on Learning from Data, July 31 - Aug 2, 2019
stingraypaper
The Stingray paper
FuzzyNumbers
Tools to Deal with Fuzzy Numbers in R
BDA_py_demos
Bayesian Data Analysis demos for Python
astrometry-inference-tutorials
Tutorials on the use of (Gaia) astrometry in astronomical data analysis or inference problems.
spdep
Spatial Dependence: Weighting Schemes, Statistics and Models
PBI
Practical Bayesian Inference
Machine-Learning-with-R-1
Datasets & solutions for Machine Learning With R by Brett Lantz
Gaia-DR2-distances
Estimate distances to stars as done for the Gaia-DR2 distance catalogue
FoFreeAST
Fourier-free Asteroseismology
learning-data-mining-with-r
Codes for the book [Learning Data Mining with R]
brinla
Bayesian Regression with INLA
uw-astr598-w18
ASTR 598: Astro-statistics and Machine Learning
parallax-tutorial-2018
Tutorials on the use of astronomical parallaxes
scikit-learn
scikit-learn: machine learning in Python
Age-maps
Hierarchical Bayesian approach for estimating physical properties in nearby galaxies: Age Maps (Paper II)
Astrostats-2017-ESAC
Material for the Astrostats 2017 course at ESAC
celerite-asteroseis
Transit fitting and basic time-domain asteroseismology using celerite and ktransit