Probabilistic Deep Learning for Real-Time Large Deformation Simulations. (arXiv:2111.01867v3 [cs.LG] UPDATED)

For many novel applications, such as patient-specific computer-aided surgery,
conventional solution techniques of the underlying nonlinear problems are
usually computationally too expensive and are lacking information about how
certain can we be about their predictions. In the present work, we propose a
highly efficient deep-learning surrogate framework that is able to accurately
predict the response of bodies undergoing large deformations in real-time. The
surrogate model has a convolutional neural network architecture, called U-Net,
which is trained with force-displacement data obtained …

arxiv deep learning learning lg probabilistic deep learning real-time simulations time