A MLP Neural Network that trains on an exoplanet dataset.
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Updated
May 22, 2023 - Python
A MLP Neural Network that trains on an exoplanet dataset.
Machine learning models and utilities for exoplanet science.
This repository contains submission for the intra-college astronomy hackathon
WebApp d'analyse des Exoplanètes afin de développer un outil de ML pour déterminer si une exoplanète est habitable ou non (Projet développé dans le cadre d'un hackathon portant sur l'Espace)
This project aims to create an engaging interactive workshop activity for secondary school students. It uses the Streamlit interface to delve into the detection and characterisation of exoplanets using simplified versions of the authentic data from current exoplanet research.
CI Milestone-2 Project: Interactive Front-end Development
This repository was created as an appendix to my final master thesis: "Detectability and occurrences in CARMENES"
Tools for end-to-end reduction of JWST exoplanet observations
Use of various machine learning models, including Deep Learning, to classify possible exoplanets from data provided by NASA.
Analyzed the lightcurve of the star TIC-239332587 and discovered dips in brightness that indicate a planet, which to my knowledge is not listed in any Exoplanet archive.
The official repository for Jux python package
taurex-emcee: automated, parallelized atmospheric retrievals with TauREx 3.1 and the emcee sampler
Checking for false positives in TESS exoplanets searches by centroid calculation in Difference Images from out-of-transit and in-transit fluxes
The objective of the project is to apply deep learning techniques in finding the existence of exoplanet. This is achieved by reducing the dimension of the data, followed by generating multiple unique models, parameter tuning of models and finally validating the model.
Exoplanet exploration using SVM with different kernels and C values. Dataset can be downloaded from Kaggle website: https://www.kaggle.com/keplersmachines/kepler-labelled-time-series-data
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