Variational Inference for Gaussian Process Models with Linear Complexity

Ching-An Cheng, Byron Boots

Nov-21-2025, 13:57:33 GMT–Neural Information Processing Systems

Large-scale Gaussian process inference has long faced practical challenges due to time and space complexity that is superlinear in dataset size.

artificial intelligence, machine learning, modeling & simulation, (14 more...)

Neural Information Processing Systems

Nov-21-2025, 13:57:33 GMT

Conferences PDF

Country:
- Asia > Middle East
  - Jordan (0.04)
- North America > United States
  - California > Los Angeles County
    - Long Beach (0.04)
  - Georgia > Fulton County
    - Atlanta (0.04)

Technology:
- Information Technology
  - Artificial Intelligence
    - Machine Learning > Statistical Learning (0.69)
    - Representation & Reasoning > Uncertainty (0.68)
    - Robots (0.93)
  - Modeling & Simulation (0.88)

Duplicate Docs Excel Report

Title
Variational Inference for Gaussian Process Models with Linear Complexity
Variational Inference for Gaussian Process Models with Linear Complexity

Similar Docs Excel Report more

Title	Similarity	Source
None found