Semantic Scholar Open Access 2019 1050 sitasi

Tackling Climate Change with Machine Learning

D. Rolnick P. Donti L. Kaack K. Kochanski Alexandre Lacoste +17 lainnya

Lihat Sumber DOI

Abstrak

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.

Topik & Kata Kunci

Computer Science Mathematics

Penulis (22)

D. Rolnick

P. Donti

L. Kaack

K. Kochanski

Alexandre Lacoste

K. Sankaran

A. Ross

Nikola Milojevic-Dupont

Natasha Jaques

Anna Waldman-Brown

A. Luccioni

Tegan Maharaj

Evan D. Sherwin

S. Mukkavilli

Konrad Paul Kording

Carla P. Gomes

Andrew Y. Ng

D. Hassabis

John C. Platt

F. Creutzig

J. Chayes

Yoshua Bengio

Format Sitasi

APA MLA BibTeX

Rolnick, D., Donti, P., Kaack, L., Kochanski, K., Lacoste, A., Sankaran, K. et al. (2019). Tackling Climate Change with Machine Learning. https://doi.org/10.1145/3485128

Akses Cepat

Lihat di Sumber doi.org/10.1145/3485128

Informasi Jurnal

Tahun Terbit: 2019
Bahasa: en
Total Sitasi: 1050×
Sumber Database: Semantic Scholar
DOI: 10.1145/3485128
Akses: Open Access ✓