Search Results for author:
Found 2 papers, 0 papers with code
Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems
Simultaneously, the INN is designed to partition the parameter vector linked to the input physical field into two distinct components: the expansion coefficients representing the forward problem solution and the Gaussian latent noise.
Deep learning based automatic segmentation of lumbosacral nerves on non-contrast CT for radiographic evaluation: a pilot study
Pixel accuracy, IoU, and Dice score are used to assess the segmentation performance of lumbosacral structures.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
