Deep‐learning based causal inference: A feasibility study based on three years of tectonic‐climate data from Moxa geodynamic observatory
W Ahmad, V Kasburg, N Kukowski… - Earth and Space …, 2024 - Wiley Online Library
Highly sensitive laser strainmeters at Moxa Geodynamic Observatory (MGO) measure
motions of the upper Earth's crust. Since the mountain overburden of the laser strainmeters …
motions of the upper Earth's crust. Since the mountain overburden of the laser strainmeters …
Embracing the black box: Heading towards foundation models for causal discovery from time series data
Causal discovery from time series data encompasses many existing solutions, including
those based on deep learning techniques. However, these methods typically do not endorse …
those based on deep learning techniques. However, these methods typically do not endorse …
Deep Learning-based Group Causal Inference in Multivariate Time-series
Causal inference in a nonlinear system of multivariate timeseries is instrumental in
disentangling the intricate web of relationships among variables, enabling us to make more …
disentangling the intricate web of relationships among variables, enabling us to make more …
Time Series Causal Link Estimation under Hidden Confounding using Knockoff Interventions
Latent variables often mask cause-effect relationships in observational data which provokes
spurious links that may be misinterpreted as causal. This problem sparks great interest in the …
spurious links that may be misinterpreted as causal. This problem sparks great interest in the …
Regime Identification for Improving Causal Analysis in Non-stationary Timeseries
Time series data from real-world systems often display non-stationary behavior, indicating
varying statistical characteristics over time. This inherent variability poses significant …
varying statistical characteristics over time. This inherent variability poses significant …