SAND: Smooth Imputation Of Sparse And Noisy Functional Data With Transformer Networks

Oct-10-2025, 21:17:04 GMT–Neural Information Processing Systems

The conventional approach to imputing longitudinal data is to employ a parametric model with mixed-effects, such as the linear mixed-effects model.

imputation, machine learning, natural language, (22 more...)

Neural Information Processing Systems

Oct-10-2025, 21:17:04 GMT

Conferences PDF

Country:
- North America > United States
  - California > Yolo County
    - Davis (0.14)
  - Massachusetts > Middlesex County
    - Cambridge (0.04)

Genre:
- Research Report > Experimental Study (1.00)

Industry:
- Health & Medicine (0.94)
- Information Technology (0.67)

Technology:
- Information Technology
  - Artificial Intelligence
    - Machine Learning
      - Neural Networks > Deep Learning (0.93)
      - Statistical Learning (0.68)
    - Natural Language (0.68)
    - Representation & Reasoning (0.67)
  - Data Science (0.94)
  - Modeling & Simulation (0.68)

Duplicate Docs Excel Report

Title
SAND: Smooth Imputation Of Sparse And Noisy Functional Data With Transformer Networks

Similar Docs Excel Report more

Title	Similarity	Source
None found