967 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Columbia UniversityUS16 papers
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)DE6 papers
- Goddard Institute for Space StudiesUS5 papers
- University of BremenDE5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- University of California, Santa CruzUS4 papers
- University of LausanneCH4 papers
- Laboratoire des Sciences du Climat et de l'EnvironnementFR3 papers
- University of California, IrvineUS3 papers
- Yale UniversityUS3 papers
- Boston UniversityUS2 papers
- CEA Paris-SaclayFR2 papers
5 papers · 1 filter
Interpretable multiscale Machine Learning-Based Parameterizations of Convection for ICON
Helge Heuer, Mierk Schwabe, Pierre Gentine +2
Machine learning (ML)-based parameterizations have been developed for Earth System Models (ESMs) with the goal to better represent subgrid-scale processes or to accelerate computat…
Generalizations of Bertrand's Postulate to Sums of Any Number of Primes
Joel E. Cohen
In 1845, Bertrand conjectured that twice any prime strictly exceeds the next prime. Tchebichef proved Bertrand's postulate in 1850. In 1934, Ishikawa proved a stronger result: the…
A benchmark for computational analysis of animal behavior, using animal-borne tags
Benjamin Hoffman, Maddie Cusimano, Vittorio Baglione +15
Animal-borne sensors (`bio-loggers') can record a suite of kinematic and environmental data, which are used to elucidate animal ecophysiology and improve conservation efforts. Mach…
Causally-informed deep learning to improve climate models and projections
Fernando Iglesias-Suarez, Pierre Gentine, Breixo Solino-Fernandez +4
Climate models are essential to understand and project climate change, yet long-standing biases and uncertainties in their projections remain. This is largely associated with the r…
Data-Driven Equation Discovery of a Cloud Cover Parameterization
Arthur Grundner, Tom Beucler, Pierre Gentine +1
A promising method for improving the representation of clouds in climate models, and hence climate projections, is to develop machine learning-based parameterizations using output…