G. Yacalis

Atmospheric Science · 2018

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Atmospheric Science — 31 citations into it; #4,108 of 4,804 by trust here, #2,243 by citations
• Global and Planetary Change — 31 citations into it; #8,612 of 10,225 by trust here, #5,211 by citations
• Artificial Intelligence — 7 citations into it

Whom G. Yacalis trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. David A. Randall (in Atmospheric Science)
2. M. Khairoutdinov (in Atmospheric Science)
3. Diederik P. Kingma (in Artificial Intelligence)
4. Jimmy Ba (in Artificial Intelligence)

Who trusts G. Yacalis

1. Chaopeng Shen (in Atmospheric Science)

Papers from G. Yacalis's perspective

Ordered by how strongly the researchers G. Yacalis trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Simulations of the Atmospheric General Circulation Using a Cloud-Resolving Model as a Superparameterization of Physical Processes
3. Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition
4. High-Resolution Simulation of Shallow-to-Deep Convection Transition over Land
5. Coupling Cloud Processes with the Large-Scale Dynamics Using the Cloud-Resolving Convection Parameterization (CRCP)
6. Deep Learning
7. Sensitivity of moist convection to environmental humidity
8. Clouds, circulation and climate sensitivity
9. Deep learning in neural networks: An overview
10. Mesoscale convective systems

Their papers

• Could Machine Learning Break the Convection Parameterization Deadlock? (2018) — 417 citations