TCD-Arena is a new customizable testing framework that runs millions of experiments to map how 33 different assumption violations affect time series causal discovery methods and shows ensembles can boost overall robustness.
Title resolution pending
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
DAG-DC-ADMM jointly clusters subjects and learns their cluster-specific causal DAGs via structural equation modeling, groupwise truncated Lasso fusion penalties, and an ADMM solver for the resulting nonconvex problem.
Introduces a regularized estimator achieving optimal MSE rates under a new relative balancedness condition while providing safety guarantees that match independent learning when tasks are unrelated.
Pilot study uses pretrained video encoder features from lung ultrasound to predict 30-day CHF readmission, finding lower-lung views and temporal differences most informative with top MLP F1 of 0.80.
citing papers explorer
-
TCD-Arena: Assessing Robustness of Time Series Causal Discovery Methods Against Assumption Violations
TCD-Arena is a new customizable testing framework that runs millions of experiments to map how 33 different assumption violations affect time series causal discovery methods and shows ensembles can boost overall robustness.
-
A Unified Framework for Structure-Aware Clustering and Heterogeneous Causal Graph Learning
DAG-DC-ADMM jointly clusters subjects and learns their cluster-specific causal DAGs via structural equation modeling, groupwise truncated Lasso fusion penalties, and an ADMM solver for the resulting nonconvex problem.
-
Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness and Safety
Introduces a regularized estimator achieving optimal MSE rates under a new relative balancedness condition while providing safety guarantees that match independent learning when tasks are unrelated.
-
Prognostic Value of Lung Ultrasound Biomarkers for Readmission Risk in Congestive Heart Failure: A Pilot Data-Driven Analysis
Pilot study uses pretrained video encoder features from lung ultrasound to predict 30-day CHF readmission, finding lower-lung views and temporal differences most informative with top MLP F1 of 0.80.