arXiv Machine Learning By Marios Andreou, Nan Chen

Bridging Prediction and Attribution: Identifying Forward and Backward Causal Influence Ranges Using Assimilative Causal Inference

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arXiv:2510. 21889v2 Announce Type: replace-cross Abstract: Causal inference identifies cause-and-effect relationships between variables.

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arXiv Statistics ML
Sep 17

A Continuous-Time Ensemble Kalman-Bucy Smoother for Causal Inference and Model Discovery

The paper presents an ensemble Kalman–Bucy smoother (EnKBS) for continuous‑time data assimilation of nonlinear dynamical systems, reconstructing conditional distributions from ensemble moments without needing tangent‑linear or adjoint models. It demonstrates that EnKBS achieves exact smoothing mean and covariance in the infinite‑ensemble limit for linear‑Gaussian systems and incorporates regularization techniques like covariance localization and inflation for high‑dimensional problems. The method is applied to Bayesian inference of causal relationships in a dyadic trigger‑feedback model and to an iterative learning algorithm that uncovers the structure and hidden parameters of a reduced‑order model of midlatitude atmospheric circulation, all with small ensembles under partial observations.

By Zhang Jiang (University of Wisconsin-Madison), Marios Andreou (University of Wisconsin-Madison), Sebastian Reich (University of Potsdam), Nan Chen (University of Wisconsin-Madison)
arXiv Machine Learning
Aug 4

Physics constraints and response validation in discrete-time reduced-order modeling: from idealized turbulent systems to climate dynamics

arXiv:2602. 13847v5 Announce Type: replace-cross Abstract: A central challenge across science and engineering is to build data-driven reduced-order models of turbulent dynamical systems that reproduce stationary statistics, predict responses to external perturbations, and remain practical for real-world applications.

By Fabrizio Falasca, Laure Zanna
arXiv Machine Learning
Aug 5

Amortized Interventional Forecasting for Multivariate CIR Processes

arXiv:2608. 03715v1 Announce Type: new Abstract: Mean-reverting dynamics are pervasive in finance, and the Cox--Ingersoll--Ross (CIR) process is a standard model for the time series they produce, from short rates to credit default swap (CDS) spreads.

By Andreas Sauter, Sumit Sourabh, Drona Kandhai, Erman Acar