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igomezv/README.md

Research interests: machine learning, Bayesian inference, and astrophysics, with a current focus on modelling stellar activity in radial-velocity and photometric data for exoplanet detection.

Open to collaborations in these areas.

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  1. ja-vazquez/SimpleMC ja-vazquez/SimpleMC Public

    Updated version of a simple MCMC code for cosmological parameter estimation where only expansion history matters.

    Python 32 33

  2. nnogada nnogada Public

    Neural Networks Optimized by Genetic Algorithms for Data Analysis

    Python 8 2

  3. doppleriann doppleriann Public

    Doppler-shift Inference with Artificial Neural Networks using Radial Velocity data

    Python 2

  4. neuralike neuralike Public

    Deep learning and genetic algorithms to speed-up Bayesian inference.

    Python 2

  5. ALP ALP Public

    Astro Layer Perceptron: nonparametric cosmological reconstructions with ANN

    Python 2 1

  6. MACS_2021_ML_basics_neural_networks MACS_2021_ML_basics_neural_networks Public

    Mini-course about artificial neural networks as part of the lecture Machine Learning Basics in the IV Mexican School of AstroCosmostatistics (MACS).

    Jupyter Notebook 5 20