Cooperative Institute for Research in the Atmosphere

output

20132025

most citedPhysically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability

324 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

I. Ebert‐Uphoff7 · h 37
E. Barnes4 · h 44
Antonios Mamalakis2 · h 10
B. Toms2 · h 16
Corey K. Potvin2 · h 5
D. Gagne2 · h 27
Lander Ver Hoef2 · h 2
A. Bostrom1 · h 43
A. Ebtehaj1 · h 20
A. McGovern1 · h 31
Amy McGovern1 · h 3
Andrew E. Schuh1 · h 3

collaborating institutions

Colorado State UniversityUS13 papers
Cooperative Institute for Research in Environmental SciencesUS5 papers
NOAA National Severe Storms LaboratoryUS3 papers
NSF National Center for Atmospheric ResearchUS3 papers
University of Colorado BoulderUS3 papers
University of OklahomaUS3 papers
Cooperative Institute for Mesoscale Meteorological StudiesUS2 papers
NOAA Global Systems Laboratory2 papers
University of MinnesotaUS2 papers
Albany State UniversityUS1 paper
Centre National de la Recherche ScientifiqueFR1 paper
École Centrale de LyonFR1 paper

Showing 2019Show all

1 paper · 1 filter

physics.ao-ph2019★ 324 cited

Physically Interpretable Neural Networks for the Geosciences: Applications to Earth System Variability

Benjamin A. Toms, Elizabeth A. Barnes, Imme Ebert-Uphoff

Neural networks have become increasingly prevalent within the geosciences, although a common limitation of their usage has been a lack of methods to interpret what the networks lea…