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| Mamba (oleku-ruumi mudel)× | TimeGPT× | |
|---|---|---|
| Valdkond | Süvaõpe | Süvaõpe |
| Perekond | Machine learning | Machine learning |
| Tekkeaasta | 2023 | 2023 |
| Looja≠ | Albert Gu | Fabio Garza |
| Tüüp | Neural network architecture | Neural network architecture |
| Algallikas≠ | Gu, A., & Dao, C. (2023). Mamba: Linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.08956. link ↗ | Garza, F., & White, C. W. (2023). TimeGPT-1: A Time Series Foundation Model. In ICML 2024 Time Series Workshop. link ↗ |
| Rööpnimetused≠ | Mamba, State space models, Selective state space | TimeGPT-1, Time series GPT |
| Seotud | 4 | 4 |
| Kokkuvõte≠ | Mamba is a sequence model architecture introduced by Gu and Dao in 2023 that achieves linear-time complexity while maintaining strong performance on language modeling tasks. By combining state space models with input-dependent selectivity, Mamba addresses the quadratic complexity of transformers while preserving modeling power. | TimeGPT is a time series foundation model introduced by Garza and White in 2023 that unifies forecasting, anomaly detection, and classification in a single pre-trained model. Inspired by large language models, TimeGPT is pre-trained on diverse time series and transfers well to downstream tasks with minimal fine-tuning. |
| ScholarGateAndmestik ↗ |
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