3 papers
cs.LG2025
One-Embedding-Fits-All: Efficient Zero-Shot Time Series Forecasting by a Model Zoo
Hao-Nan Shi, Ting-Ji Huang, Lu Han +2
The proliferation of Time Series Foundation Models (TSFMs) has significantly advanced zero-shot forecasting, enabling predictions for unseen time series without task-specific fine-…
cs.LG2025
DConAD: A Differencing-based Contrastive Representation Learning Framework for Time Series Anomaly Detection
Wenxin Zhang, Xiaojian Lin, Wenjun Yu +7
Time series anomaly detection holds notable importance for risk identification and fault detection across diverse application domains. Unsupervised learning methods have become pop…
q-fin.CP2024
AlphaForge: A Framework to Mine and Dynamically Combine Formulaic Alpha Factors
Hao Shi, Weili Song, Xinting Zhang +5
The complexity of financial data, characterized by its variability and low signal-to-noise ratio, necessitates advanced methods in quantitative investment that prioritize both perf…