Showing stat.MLShow all
2 papers · 1 filter
stat.ML2026
Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects
Hao Wang, Licheng Pan, Qingsong Wen +12
Autocorrelation is a defining characteristic of time-series data, where each observation is statistically dependent on its predecessors. In the context of deep time-series forecast…
stat.ML2026
Observationally Informed Adaptive Causal Experimental Design
Erdun Gao, Liang Zhang, Jake Fawkes +5
Randomized Controlled Trials (RCTs) represent the gold standard for causal inference yet remain a scarce resource. While large-scale observational data is often available, it is ut…