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Google Research releases TimesFM 3.0 for time-series forecasting

By PulseAugur Editorial · [1 sources] ·

Google Research has released TimesFM 3.0, a new time-series foundation model built on a Stacked Mixing Transformer architecture. This model is designed for time-series forecasting and utilizes a decoder-only approach. It has been pretrained on a variety of data sources, including Wikipedia pageviews and Google Trends, and features 20 transformer layers with a model dimension of 1280. AI

IMPACT This release provides a new foundation model for time-series forecasting, potentially improving accuracy and efficiency in applications relying on temporal data analysis.

RANK_REASON Release of a new foundation model for time-series forecasting with associated paper. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Trending Models →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Google Research releases TimesFM 3.0 for time-series forecasting

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Release of a new foundation model for time-series forecasting with associated paper. [lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release, paper
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High
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32 days old
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COVERAGE [1]

  1. Hugging Face Trending Models TIER_1 English(EN) · google ·

    google/timesfm-3.0-pytorch

    time-series-forecasting · 0 downloads · 100 likes

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