3 citations · 5 across the 5 of their papers we have counts for
4 papers · 1 filter
BITS: Rethinking Fair and Comprehensive Evaluation for Irregular Time Series Forecasting
Kangjia Yan, Linfeng Wang, Tianen Shen +7
Despite recent progress in irregular time series forecasting, the field still lacks a unified benchmark for fair and comprehensive evaluation. Existing evaluations are often conduc…
Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework
Tianen Shen, Zhengyu Li, Yutong Li +4
Irregular multivariate time series are widely encountered in applications such as healthcare monitoring, human activity recognition, and environmental sensing. Their core challenge…
SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement
Xiangfei Qiu, Xvyuan Liu, Tianen Shen +4
Time series forecasting is important in many fields that require accurate predictions for decision-making. Patching techniques, commonly used and effective in time series modeling,…
CoDiM: Learning with Noisy Labels via Contrastive Semi-Supervised Learning
Xin Zhang, Zixuan Liu, Kaiwen Xiao +5
Labels are costly and sometimes unreliable. Noisy label learning, semi-supervised learning, and contrastive learning are three different strategies for designing learning processes…