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Tackling Climate Change with Machine Learning

delete2022-02-07
delete263
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OA
AI
D
David Rolnick *
P
Priya L. Donti
L
Lynn H. Kaack
K
Kelly Kochanski
A
Alexandre Lacoste
K
Kris Sankaran
A
Andrew Slavin Ross
N
Nikola Milojevic-Dupont
N
Natasha Jaques
A
Anna Waldman‐Brown
A
Alexandra Sasha Luccioni
T
Tegan Maharaj
E
Evan David Sherwin
S
S. Karthik Mukkavilli
K
Konrad P. Körding
C
Carla P. Gomes
A
Andrew Y. Ng
D
Demis Hassabis
J
John Platt
F
Felix Creutzig
J
Jennifer Chayes
Y
Yoshua Bengio
DOI:10.1145/3485128delete
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摘要

摘要

En 中文
Climate change is one of the greatest challenges facing humanity, and we, as machine learning (ML) experts, may wonder how we can help. Here we describe how ML can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by ML, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the ML community to join the global effort against climate change.
Keyword:
Climate change
mitigation
adaptation
machine learning
artificial intelligence

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university of wisconsin madison
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Carnegie Mellon University
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论文数: 1.4W
被引数: 2.7W
U
University of California Berkeley
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论文数: 2.8W
被引数: 11.3W
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New York University
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论文数: 3.9W
被引数: 5.8W
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Stanford University
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university of pennsylvania
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Technical University of Berlin
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1.3W
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University of Wisconsin System
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ETH Zurich
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Lawrence Berkeley National Laboratory
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united states department of energy (doe)
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swiss federal institutes of technology domain
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Polytechnique Montreal
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university of colorado boulder
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McGill University
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