TimeSeek pretrains one model for multi-task time series analytics
After large-scale pretraining, authors report state-of-the-art forecasting, anomaly detection, and classification in few-shot and zero-shot settings.
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Stories tagged #multi-task-learning
HorizON predicts cycle-by-cycle properties of organic battery stacks
One multi-fidelity model learns DFT redox potentials and specific-capacity trajectories from full stack representations.
UniH^3: Unifying Hierarchical Homogeneity and Heterogeneity for All-in-One Medical Image Restoration
UniH3 unifies hierarchical homogeneity and heterogeneity modeling for all-in-one medical image restoration across modalities and degradation types.
Multi-Task Learning for Sparsely-Labeled Time Series: A Case Study on Cold-Hardiness Modeling
Multi-task RNN architectures pooling sparse cultivar data improve grape cold-hardiness and budbreak prediction over single-task and scientific baselines.