ML for Exoplanet Detection Review

This project involved a comprehensive literature review of the application of machine learning and deep learning models for analyzing light curve data from NASA's TESS and Kepler missions to detect exoplanets.

Key Areas of Research

• Analyzed state-of-the-art techniques, including LSTMs and WaveCeptionNet, for their effectiveness in signal detection.
• Investigated methods for addressing common challenges such as stellar variability, instrumental noise, and the scalability of data processing.
• The resulting paper provides a detailed overview of the field, highlighting successful models and outlining future research directions.