BenchFlux: Scalable AI Benchmarks for Terrestrial Carbon Fluxes to Advance Research, Education, and Resource Management
BenchFlux: Scalable AI Benchmarks for Terrestrial Carbon Fluxes to Advance Research, Education, and Resource Management
Stefan Metzger1, Maoya Bassiouni2, Samuel Bower1, Ankur R Desai3, Matthew Fortier4, Sophie Hoffman5, Yanghui Kang6, Trevor Keenan2, Danielle Losos7, Alvaro Moreno8, Christopher Pal9, Sadegh Ranjbar, PhD Candidate10, Oliver Sonnentag11, Paul C Stoy12, Emma Izquierdo13 and Jingfeng Xiao14, (1)AtmoFacts, Longmont, United States, (2)University of California, Berkeley, Department of Environmental Science, Policy, and Management, Berkeley, United States, (3)University of Wisconsin Madison, Atmospheric and Oceanic Sciences, Madison, United States, (4)Mila - Quebec Artificial Intelligence Institute, Montreal, Canada, (5)University of Wisconsin Madison, Biological System Engineering, Madison, United States, (6)Virginia Tech, Department of Biological Systems Engineering, Blacksburg, Virginia, United States, (7)Yale University, New Haven, United States, (8)Image Processing Laboratory, Universitat de València, Paterna, Spain, (9)Ecole Polytechnique de Montreal, Computer Engineering and Software Engineering, Montreal, Canada, (10)University of Wisconsin Madison, Biological Systems Engineering, Madison, WI, United States, (11)University of Montreal, Département de Géographie, Montreal, QC, Canada, (12)University of Wisconsin-Madison, Madison, Biological Systems Engineering, Madison, United States, (13)BOKU University, Institute of Geomatics, Vienna, Austria, (14)University of New Hampshire, Institute for the Study of Earth, Oceans, and Space, Earth Systems Research Center, Durham, United States