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Found 5 papers, 1 papers with code
Active Learning-Based Multistage Sequential Decision-Making Model with Application on Common Bile Duct Stone Evaluation
For both simulation and testing cohorts, the proposed method is more effective, stable, interpretable, and computationally efficient on parameter estimation.
APIK: Active Physics-Informed Kriging Model with Partial Differential Equations
We present in this work a PDE Informed Kriging model (PIK), which introduces PDE information via a set of PDE points and conducts posterior prediction similar to the standard kriging method.
Additive Tensor Decomposition Considering Structural Data Information
In this paper, we provide a new definition of structural information in tensor data.
Active Image Synthesis for Efficient Labeling
The great success achieved by deep neural networks attracts increasing attention from the manufacturing and healthcare communities.
Generative Invertible Networks (GIN): Pathophysiology-Interpretable Feature Mapping and Virtual Patient Generation
Machine learning methods play increasingly important roles in pre-procedural planning for complex surgeries and interventions.
