Causal inference for time series
Many research questions in Earth and environmental sciences are inherently causal,
requiring robust analyses to establish whether and how changes in one variable cause …
requiring robust analyses to establish whether and how changes in one variable cause …
Inferring causation from time series in Earth system sciences
The heart of the scientific enterprise is a rational effort to understand the causes behind the
phenomena we observe. In large-scale complex dynamical systems such as the Earth …
phenomena we observe. In large-scale complex dynamical systems such as the Earth …
Detecting and quantifying causal associations in large nonlinear time series datasets
Identifying causal relationships and quantifying their strength from observational time series
data are key problems in disciplines dealing with complex dynamical systems such as the …
data are key problems in disciplines dealing with complex dynamical systems such as the …
A survey of learning causality with data: Problems and methods
This work considers the question of how convenient access to copious data impacts our
ability to learn causal effects and relations. In what ways is learning causality in the era of …
ability to learn causal effects and relations. In what ways is learning causality in the era of …
Spatio-temporal data mining: A survey of problems and methods
Large volumes of spatio-temporal data are increasingly collected and studied in diverse
domains, including climate science, social sciences, neuroscience, epidemiology …
domains, including climate science, social sciences, neuroscience, epidemiology …
Machine learning for the geosciences: Challenges and opportunities
Geosciences is a field of great societal relevance that requires solutions to several urgent
problems facing our humanity and the planet. As geosciences enters the era of big data …
problems facing our humanity and the planet. As geosciences enters the era of big data …
Attributable human‐induced changes in the likelihood and magnitude of the observed extreme precipitation during Hurricane Harvey
Record rainfall amounts were recorded during Hurricane Harvey in the Houston, Texas,
area, leading to widespread flooding. We analyze observed precipitation from the Global …
area, leading to widespread flooding. We analyze observed precipitation from the Global …
Identifying causal gateways and mediators in complex spatio-temporal systems
Identifying regions important for spreading and mediating perturbations is crucial to assess
the susceptibilities of spatio-temporal complex systems such as the Earth's climate to …
the susceptibilities of spatio-temporal complex systems such as the Earth's climate to …
Evaluation methods and measures for causal learning algorithms
The convenient access to copious multifaceted data has encouraged machine learning
researchers to reconsider correlation-based learning and embrace the opportunity of …
researchers to reconsider correlation-based learning and embrace the opportunity of …
Using causal effect networks to analyze different Arctic drivers of midlatitude winter circulation
In recent years, the Northern Hemisphere midlatitudes have suffered from severe winters
like the extreme 2012/13 winter in the eastern United States. These cold spells were linked …
like the extreme 2012/13 winter in the eastern United States. These cold spells were linked …