A Python package for calculating detection limits for exoplanet high contrast imaging (HCI) datasets.

Predicting potential exoplanets in star systems using light intensity curves data derived from observations made by the NASA Kepler space telescope.

The project aims to leverage machine learning techniques to analyse the flux data and accurately classify stars as either exoplanet-hosting or non-exoplanet-hosting. By training a model on the provided dataset, we seek to uncover patterns and features indicative of exoplanet presence, enabling the model to make predictions on unseen data.

Half-Sibling Regression for High-Contrast Imaging

Matlab code for the adaptive annealed importance sampling based marginal likelihood estimator.

Direct Exoplanet Imaging with Tensor Decompositions

Algoritmos para o tratamento de curvas de luz, treinamento e utilização de modelos de Machine Learning para a detecção automatizada de exoplanetas.

PLATO WP36 Exoplanet Analysis System transit detection pipeline (version 1)

PANOTPES Observatory Control Software for a telescope build using a moxa UC-8112A-ME series arm processor.

The MASER (Magnetically interActing Stars and Exoplanets in the Radio) code developed by Kavanagh & Vedantham (2023).

Find out if there are new planets using Deep Learning

Code for participation in IIT Kharagpur 2018 inter-iit tech meet competition on exoplanet detection with time-series analysis.

Master’s Thesis. Predicting stellar parameters to detect nearby exoplanets using a deep learning approach on billions of data points.

A culmination of the tasks I will be undertaking as part of a PhD project around the TOLIMAN mission.

Unsupervised deep learning for exoplanet detection

This repository contains submission for the intra-college astronomy hackathon

Public repository of our works in Exoplanet analysis with Deep Learning

Public Repository for Exoplanet Detection with Classical Machine Learning Approaches

Installation bundles for EXOTIC (https://github.com/rzellem/EXOTIC)

PlanetFinder is a Python-based tool designed for the detection and analysis of exoplanets using light curve data from the TESS mission. Leveraging the Lightkurve library, it allows users to search for, visualize, and analyze potential exoplanet transits, making it an ideal resource for both citizen scientists and professional astronomers.