Modeling Molecular Complexity: Building a Novel Multidisciplinary Machine Learning Framework to Understand Molecular Synthesis and Signatures
- ADS bibcode
- 2022AGUFMIN22D0334H
- year
- 2022
- Listed Authors
- Hastings, Jaden J. A.
- Bell, Aaron C.
- Gebhard, Timothy
- Gong, Jian
- Baydin, Atılım Güneş
- Fricke, Matthew
- Mascaro, Massimo
- Phillips, Michael
- Warren-Rhodes, Kimberly
- Cabrol, Nathalie A.
- Listed Institutions
- XO.LABS, Los Angeles, United States
- The University of Tokyo, Tokyo, Japan
- Max Planck Institute for Intelligent Systems, Tübingen, Germany
- Massachusetts Institute of Technology, Cambridge, United States
- University of Oxford, Oxford, United Kingdom
- University of New Mexico, Albuquerque, United States
- Google, Mountain View, United States
- University of Northern Colorado, Greeley, United States
- SETI Institute Mountain View, Mountain View, United States
- SETI Institute, Mountain View, United States
Linked Authors [?]
Linked Institutions