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Found 5 papers, 1 papers with code
Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems
We show that a trained neural operator with error correction can achieve a quadratic reduction of its approximation error, all while retaining substantial computational speedups of posterior sampling when models are governed by highly nonlinear PDEs.
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport
We tackle this challenging Bayesian inference problem using a likelihood-free approach based on measure transport together with the construction of summary statistics for the image data.
A 1D-0D-3D coupled model for simulating blood flow and transport processes in breast tissue
In this work, we present mixed dimensional models for simulating blood flow and transport processes in breast tissue and the vascular tree supplying it.
Quantitative in vivo imaging to enable tumor forecasting and treatment optimization
Current clinical decision-making in oncology relies on averages of large patient populations to both assess tumor status and treatment outcomes.
Modeling and simulation of vascular tumors embedded in evolving capillary networks
The flow in the blood vessels is controlled by Poiseuille flow, and Starling's law is applied to model the mass transfer in and out of blood vessels.
