Standout Papers

Making the Black Box More Transparent: Understanding the Physical Implications of Machine Learning 2019 2026 2021 2023 315
  1. Making the Black Box More Transparent: Understanding the Physical Implications of Machine Learning (2019)
    Amy McGovern, Ryan Lagerquist et al. Bulletin of the American Meteorological Society

Immediate Impact

26 from Science/Nature 69 standout
Sub-graph 1 of 24

Citing Papers

Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems
2024 Standout
The Rise of Data-Driven Weather Forecasting: A First Statistical Assessment of Machine Learning–Based Weather Forecasts in an Operational-Like Context
2024 Standout
5 intermediate papers

Works of Ryan Lagerquist being referenced

Making the Black Box More Transparent: Understanding the Physical Implications of Machine Learning
2019 Standout
Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather
2017
and 1 more

Author Peers

Author Last Decade Papers Cites
Ryan Lagerquist 645 580 123 265 19 943
Suman Ravuri 551 438 173 208 8 975
Peter Dueben 695 590 147 253 26 1.0k
Antonello Pasini 397 489 83 167 57 1.1k
Maria Athanassiadou 485 399 62 165 12 780
D. D. Lucas 559 550 83 172 40 936
Mikdat Kadıoğlu 234 444 76 226 30 820
Seyd Teymoor Seydi 304 381 95 173 49 983
Jeong-Hwan Kim 503 536 66 205 7 837
Wai Kin Wong 661 575 82 211 44 934
T. J. Schmugge 387 434 52 483 21 818

All Works

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2026