Theory-Guided Data Science for Climate Change

By James H. Faghmous, Arindam Banerjee, Shashi Shekhar, Michael S. Steinbach, Vipin Kumar, Auroop Ratan Ganguly, Nagiza F. Samatova. 2014

33 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Atmospheric Science, Global and Planetary Change

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yong Xiang
2. Song Guo
3. Jinsong Wu
4. Trond Kvamsdal
5. Huawei Huang
6. Omer San
7. Adil Rasheed

In Atmospheric Science

1. Trond Kvamsdal
2. Omer San
3. Adil Rasheed

Citations in the corpus

• Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data (2016, neutral): “These efforts have been complemented with recent review papers [8], [31], [32], [33], workshops (e.”
• Information and Communications Technologies for Sustainable Development Goals: State-of-the-Art, Needs and Perspectives (2018, background): “the spatio-temporal and physical nature of climate phenomena [166] are in urgent need.”
• Digital Twin: Values, Challenges and Enablers From a Modeling Perspective (2019, background): “, please see [366]–[370] for promoting theory-guided ML in various disciplines).”