Code and Data for "A Machine Learning Approach to Exoplanet Atmospheric Retrieval: Application to Optical Filter Ranking"
Munsaket, Patcharawee;
Code and Data for "A Machine Learning Approach to Exoplanet Atmospheric Retrieval: Application to Optical Filter Ranking"
This is the initial release containing the Python code, Jupyter Notebooks (with HTML renderings), and synthetic transmission datasets (Pickle files) accompanying the manuscript: "A Machine Learning Approach to Exoplanet Atmospheric Retrieval: Application to Optical Filter Ranking", accepted for publication in The Astronomical Journal.
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
selected citations
Citations provided by BIP!
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP! 0
Average
Average
Average