4 papers · 1 filter
The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction
Shu Wan, Abhinav Gorantla, Huan Liu +2
Under standard graphical assumptions, the Markov boundary of a target variable is the smallest set of features that renders every other feature redundant. Once the boundary is obse…
Causality by Abstraction: Symbolic Rule Learning in Multivariate Timeseries with Large Language Models
Preetom Biswas, Giulia Pedrielli, K. Selçuk Candan
Inferring causal relations in timeseries data with delayed effects is a fundamental challenge, especially when the underlying system exhibits complex dynamics that cannot be captur…
CauSTream: Causal Spatio-Temporal Representation Learning for Streamflow Forecasting
Shu Wan, Reepal Shah, John Sabo +2
Streamflow forecasting is crucial for water resource management and risk mitigation. While deep learning models have achieved strong predictive performance, they often overlook und…
Cross-Domain Conditional Diffusion Models for Time Series Imputation
Kexin Zhang, Baoyu Jing, K. Selçuk Candan +4
Cross-domain time series imputation is an underexplored data-centric research task that presents significant challenges, particularly when the target domain suffers from high missi…