ScholarGate
المساعد

قارن الطرق

راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.

TimeGPT×مامبا (نموذج فضاء الحالة)×
المجالالتعلم العميقالتعلم العميق
العائلةMachine learningMachine learning
سنة النشأة20232023
صاحب الطريقةFabio GarzaAlbert Gu
النوعNeural network architectureNeural network architecture
المصدر التأسيسيGarza, F., & White, C. W. (2023). TimeGPT-1: A Time Series Foundation Model. In ICML 2024 Time Series Workshop. link ↗Gu, A., & Dao, C. (2023). Mamba: Linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.08956. link ↗
الأسماء البديلةTimeGPT-1, Time series GPTMamba, State space models, Selective state space
ذات صلة44
الملخصTimeGPT 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.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.
ScholarGateمجموعة البيانات
  1. v1
  2. 1 المصادر
  3. PUBLISHED
  1. v1
  2. 1 المصادر
  3. PUBLISHED

انتقل إلى البحث تنزيل الشرائح

ScholarGateقارن الطرق: TimeGPT · Mamba (State Space Model). استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare