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مامبا (نموذج فضاء الحالة)×TimeGPT×
المجالالتعلم العميقالتعلم العميق
العائلةMachine learningMachine learning
سنة النشأة20232023
صاحب الطريقةAlbert GuFabio Garza
النوعNeural network architectureNeural network architecture
المصدر التأسيسيGu, 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 ↗
الأسماء البديلةMamba, State space models, Selective state spaceTimeGPT-1, Time series GPT
ذات صلة44
الملخصMamba 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.
ScholarGateمجموعة البيانات
  1. v1
  2. 1 المصادر
  3. PUBLISHED
  1. v1
  2. 1 المصادر
  3. PUBLISHED

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ScholarGateقارن الطرق: Mamba (State Space Model) · TimeGPT. استُرجع بتاريخ 2026-06-19 من https://scholargate.app/ar/compare