TimesFM
PulseAugur coverage of TimesFM — every cluster mentioning TimesFM across labs, papers, and developer communities, ranked by signal.
- 2025-09-23 research_milestone Google Research presented a new method for time-series foundation models to perform few-shot learning at inference time. source
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New framework distills foundation models for specialized time-series forecasting
Researchers have developed a novel framework called Guard to distill knowledge from large, general-purpose foundation models (FMs) into lightweight, specialized time-series forecasters. This approach addresses the chall…
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Study Compares AI Architectures for Mobile Health Forecasting
A new study compares six deep learning architectures, two Foundation Models (FM), and statistical baselines for multi-horizon behavioral forecasting using mobile health data. The research found that no single architectu…
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New benchmark evaluates time-series models for glucose forecasting
Researchers have introduced GlucoFM-Bench, a new benchmark designed to evaluate time-series foundation models (TSFMs) for blood glucose forecasting. The study assessed eight different model architectures, including pre-…
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TimesFM foundation model enhances cyber-physical attack detection
Researchers have developed a novel method for detecting attacks in cyber-physical systems using a time-series foundation model called TimesFM. This approach does not require prior knowledge of the system's model or stru…
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TopoPrimer framework boosts forecasting accuracy with topological context
Researchers have developed TopoPrimer, a novel framework designed to enhance forecasting models by incorporating the global topological structure of time series data. This approach utilizes persistent homology and spect…
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ISOMORPH digital twin offers new benchmarks for supply chain forecasting
Researchers have introduced ISOMORPH, a novel digital twin designed for supply chain logistics, addressing a gap in existing time-series forecasting benchmarks. This simulator offers a configurable, multi-echelon networ…
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Google Research enhances time-series forecasting with few-shot learning
Google Research has developed a new method to enhance time-series forecasting models by enabling them to learn from a few examples at inference time. This approach, called In-Context Fine-Tuning (ICF), builds upon their…