November 21, 2025Annual Review of Statistics and Its Application

Operator Learning: A Statistical Perspective

View Full Paper

Ask AI

Bookmark

Authors

USUnique Subedi ATAmbuj Tewari

Discussion

Member takes

Implication

Operator learning reveals surrogate models for partial differential equations, highlighting architecture design and uncertainty quantification frameworks.

Key Points

Surrogate models reduce the complexity of partial differential equations in various applications.
Key developments include approaches incorporating physical and mathematical constraints in architecture design.
Observational analysis with mathematical models assists in deriving insight from experimental data.
Supports advancements in active data collection for improved uncertainty quantification frameworks.

Cite This Study

Subedi et al. (2025) studied this question.

synapsesocial.com/papers/6924e405c0ce034ddc34f8b6 https://doi.org/10.1146/annurev-statistics-042424-070908

View Full Paper

Ask AI

Bookmark

Implication

Operator learning reveals surrogate models for partial differential equations, highlighting architecture design and uncertainty quantification frameworks.

Operator Learning: A Statistical Perspective

Discussion

Member takes

Implication

Key Points

Cite This Study

Operator Learning: A Statistical Perspective

Discussion

Member takes

Implication

Key Points

Cite This Study

Also Consider

Also Consider