Towards Universal Representation-Based Process Control

arXiv:2609.30790 · cs.LG · Submitted 2026-09-25 · Read on arXiv

cs.LG

Submitted: 2026-09-25

Updated: 2026-09-25

Code: https://github.com/moment-timeseries-foundation-model/moment3https:

Terminology

• Calibration — 56× in this paper · explained in 7 episodes
• AUC — 36× in this paper · explained in 2 episodes
• Consistency — 22× in this paper · explained in 3 episodes
• Ablation — 14× in this paper · explained in 1 episode
• Foundation Model — 7× in this paper · explained in 3 episodes
• Ablation study — 6× in this paper · explained in 1 episode
• Foundation Models — 6× in this paper · explained in 7 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• Embeddings — 5× in this paper · explained in 2 episodes
• Fine-Tuning — 5× in this paper · explained in 5 episodes
• Non-stationarity — 4× in this paper · explained in 2 episodes
• Representation Learning — 4× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Dandawate and Giannakis — 3× in this paper
• Ablation Studies — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Distribution Shift — 2× in this paper · explained in 5 episodes
• Exchangeability — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Linear Discriminant Analysis — 2× in this paper
• Synthetic Data Generation — 2× in this paper · explained in 5 episodes
• Time Series Forecasting — 2× in this paper · explained in 3 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Concept Drift — 1× in this paper · explained in 4 episodes
• Conformal Prediction — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Mixture of Experts — 1× in this paper · explained in 2 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• Chronos-2: From Univariate to Universal Forecasting
• TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning
• Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts

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