2 papers
cs.LG2025
Contrastive Time Series Forecasting with Anomalies
Joel Ekstrand, Zahra Taghiyarrenani, Slawomir Nowaczyk
Time series forecasting predicts future values from past data. In real-world settings, some anomalous events have lasting effects and influence the forecast, while others are short…
cs.LG2025
Weighted Contrastive Learning for Anomaly-Aware Time-Series Forecasting
Joel Ekstrand, Tor Mattsson, Zahra Taghiyarrenani +3
Reliable forecasting of multivariate time series under anomalous conditions is crucial in applications such as ATM cash logistics, where sudden demand shifts can disrupt operations…