2 papers
cs.LG2025
TopoCL: Topological Contrastive Learning for Time Series
Namwoo Kim, Hyungryul Baik, Yoonjin Yoon
Universal time series representation learning is challenging but valuable in real-world applications such as classification, anomaly detection, and forecasting. Recently, contrasti…
cs.LG2025
MobiCLR: Mobility Time Series Contrastive Learning for Urban Region Representations
Namwoo Kim, Takahiro Yabe, Chanyoung Park +1
Recently, learning effective representations of urban regions has gained significant attention as a key approach to understanding urban dynamics and advancing smarter cities. Exist…