4 citations · 7 across the 9 of their papers we have counts for
10 papers
Causal Fingerprints Reveal Hidden Mechanisms in Partially-Observed Dynamical Systems
Zhang Jiang, Marios Andreou, Nan Chen
In partially-observed dynamical systems, distinct hidden mechanisms can produce similar observable summary statistics while explaining individual events differently. We introduce c…
TianJi-Environ: An Autonomous AI Scientist for Atmospheric Environmental Research
Haoluo Zhao, Hongchun Zhang, Nan Li +6
As atmospheric environmental prediction continues to improve, interpretable validation of pollution mechanisms and feedback processes has become a main challenge in atmospheric che…
Mechanisms and Pathways of Extreme Events in Partially-Observed Stochastic Dynamical Systems
Charlotte Moser, Nan Chen, Marios Andreou
Extreme events occur across the natural, engineering, and socioeconomic sciences, where rare but high-impact episodes can lead to disproportionate consequences that pose major chal…
A Continuous-Time Ensemble Kalman-Bucy Smoother for Causal Inference and Model Discovery
Zhang Jiang, Marios Andreou, Sebastian Reich +1
Data assimilation (DA) integrates observational information with model predictions to improve state estimation in complex systems. While filtering provides the basis for online for…
Bridging Prediction and Attribution: Identifying Forward and Backward Causal Influence Ranges Using Assimilative Causal Inference
Marios Andreou, Nan Chen
Causal inference identifies cause-and-effect relationships between variables. While traditional approaches rely on data to reveal causal links, a recently developed method, assimil…
Assimilative Causal Inference
Marios Andreou, Nan Chen, Erik Bollt
Causal inference is fundamental across scientific disciplines, yet existing methods struggle to capture instantaneous, time-evolving causal relationships in complex, high-dimension…
An Adaptive Online Smoother with Closed-Form Solutions and Information-Theoretic Lag Selection for Conditional Gaussian Nonlinear Systems
Marios Andreou, Nan Chen, Yingda Li
Data assimilation (DA) combines partial observations with dynamical models to improve state estimation. Filter-based DA uses only past and present data and is the prerequisite for…
A Martingale-Free Introduction to Conditional Gaussian Nonlinear Systems
Marios Andreou, Nan Chen
The conditional Gaussian nonlinear system (CGNS) is a broad class of nonlinear stochastic dynamical systems. Given the trajectories for a subset of state variables, the remaining f…
Taming Uncertainty in a Complex World: The Rise of Uncertainty Quantification -- A Tutorial for Beginners
Nan Chen, Stephen Wiggins, Marios Andreou
This paper provides a tutorial about uncertainty quantification (UQ) for those who have no background but are interested in learning more in this area. It exploits many very simple…
Statistical Response of ENSO Complexity to Initial Condition and Model Parameter Perturbations
Marios Andreou, Nan Chen
Studying the response of a climate system to perturbations has practical significance. Standard methods in computing the trajectory-wise deviation caused by perturbations may suffe…