Granite TimeSeries TSPulse R1 Model Card 🚀 Update (Mar 2026): TSPulse has been accepted at ICLR 2026. TSPulse models are ultra compact pre trained models for time series data, featuring just 1M parameters and supporting GPU free inference . Designed for versatility, TSPulse excels across a wide range of tasks including classification , anomaly detection (AD) , imputation , and similarity search . At the architecture level, TSPulse introduces a novel dual space masked reconstruction strategy that learns jointly from both time and frequency domains — capturing complementary patterns in a unified embedding space. This is coupled with a dual embedding disentanglement mechanism that produces both fine grained embeddings for detailed analysis and semantic embeddings for broader understanding. These semantic embeddings are inherently robust to variations in time, magnitude, and noise, making them ideal for time series retrieval. At the task level, TSPulse integrates several innovations: TSLens : A fine tuning module for task aware feature extraction. Multi head triangulation : Fuses outputs from multiple prediction streams to enhance anomaly detection robustness. Hybrid masking : Reduces…
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