เปรียบเทียบวิธี

	Sundial: แบบจำลองพื้นฐานอนุกรมเวลาแบบก่อกำเนิด	Moirai: แบบจำลองพื้นฐานสำหรับการพยากรณ์อนุกรมเวลาแบบสากล
สาขาวิชา	การเรียนรู้เชิงลึก	การเรียนรู้เชิงลึก
ตระกูล	Machine learning	Machine learning
ปีกำเนิด	2025	2024
ผู้ริเริ่ม	Yong Liu et al. (Tsinghua)	Gerald Woo et al. (Salesforce)
ประเภท	Generative time-series foundation model family	Foundation model for zero-shot time-series forecasting
แหล่งต้นตำรับ	Liu, Y., Qin, G., Shi, X., Hu, T., Wang, J., & Long, M. (2025). Sundial: A family of highly capable time series foundation models. ICML.	Woo, G., Liu, C., Kumar, A., Xiong, C., Savarese, S., & Sahoo, D. (2024). Unified training of universal time series forecasting transformers. ICML.
ชื่อเรียกอื่น	Sundial TSF, Time-Series Foundation Model (Generative), Sundial ICML 2025, Zaman Serisi Temel Modeli (Sundial)	Unified Time-Series Transformer, Universal Forecasting Transformer, MOIRAI, Evrensel Zaman Serisi Tahmin Transformatörü
ที่เกี่ยวข้อง	3	3
สรุป	Sundial is a family of generative time-series foundation models introduced by Yong Liu and colleagues at Tsinghua University (ICML 2025). Pre-trained on large and diverse time-series corpora, Sundial employs a decomposition-based architecture paired with a generative forecasting head to produce probabilistic multi-horizon forecasts. It represents a shift toward general-purpose, zero-shot-capable models for real-world temporal prediction tasks.	Moirai is a foundation model for universal time-series forecasting introduced by Gerald Woo and colleagues at Salesforce Research in 2024 and presented at ICML. The core idea is to pre-train a single large Transformer on an exceptionally diverse corpus of time-series data (LOTSA) spanning many domains and frequencies, enabling zero-shot and few-shot forecasting on unseen datasets without task-specific retraining. Moirai employs patch-based tokenization, any-variate attention, and a mixture-of-distributions output head to handle variable frequencies, multiple variates, and probabilistic prediction in a unified architecture.