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AntTech
AntTech
Mar 5, 2025 · Artificial Intelligence

Pyraformer: Low-Complexity Pyramidal Attention for Long-Range Time Series Modeling and Forecasting

Pyraformer introduces a pyramidal attention mechanism that captures long-range dependencies in time-series data with linear time and space complexity, achieving state-of-the-art forecasting accuracy on multiple real-world datasets while reducing computational cost, as demonstrated in extensive ICLR-2022 experiments.

ICLR 2022Pyraformerdeep learning
0 likes · 11 min read
Pyraformer: Low-Complexity Pyramidal Attention for Long-Range Time Series Modeling and Forecasting
AntTech
AntTech
Apr 27, 2022 · Artificial Intelligence

Pyraformer: Low-Complexity Pyramidal Attention for Long-Range Time Series Modeling and Forecasting

The paper introduces Pyraformer, a low‑complexity pyramidal‑attention Transformer that captures multi‑scale temporal dependencies with linear time‑space complexity, achieving superior single‑step and long‑range forecasting performance on real‑world datasets while supporting green‑computing capacity management.

PyraformerTransformerlong-range dependencies
0 likes · 14 min read
Pyraformer: Low-Complexity Pyramidal Attention for Long-Range Time Series Modeling and Forecasting