Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models

Chris Oates, Steven Niederer, Angela Lee, François-Xavier Briol, Mark Girolami

Nov-21-2025, 11:56:42 GMT–Neural Information Processing Systems

The computational model can be assessed through comparison of these predictions to test data generated from an experiment.

assessment, eqn, numerical error, (13 more...)

Neural Information Processing Systems

Nov-21-2025, 11:56:42 GMT

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Country:
- North America > United States
  - California > Los Angeles County > Long Beach (0.04)
- Asia > Japan
  - Honshū > Kantō > Kanagawa Prefecture (0.04)

Genre:
- Research Report (1.00)

Industry:
- Health & Medicine > Therapeutic Area > Cardiology/Vascular Diseases (0.68)

Technology:
- Information Technology > Artificial Intelligence
  - Representation & Reasoning > Uncertainty
    - Bayesian Inference (0.93)
  - Machine Learning > Learning Graphical Models
    - Directed Networks > Bayesian Learning (0.93)

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Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models

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