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Found 3 papers, 1 papers with code
Ancestral causal learning in high dimensions with a human genome-wide application
We focus on the setting in which some causal (ancestral) relationships are known (via background knowledge or experimental data) and put forward a general approach that scales to large problems.
Fast Parameter Inference in a Biomechanical Model of the Left Ventricle using Statistical Emulation
Emulation methods avoid computationally expensive simulations from the LV model by replacing the biomechanical model, which is defined in terms of explicit partial differential equations, with a surrogate model inferred from simulations generated before the arrival of a patient, vastly improving computational efficiency at the clinic.
Applications Methodology
On a New Improvement-Based Acquisition Function for Bayesian Optimization
Bayesian optimization (BO) is a popular algorithm for solving challenging optimization tasks.
