Tian Shen

BITS: Rethinking Fair and Comprehensive Evaluation for Irregular Time Series Forecasting

Despite recent progress in irregular time series forecasting, the field still lacks a unified benchmark for fair and comprehensive evaluation. Existing evaluations are often conducted on a limited set of datasets with inconsistent experimental protocols and predominantly error-based metrics, rendering it difficult to c...