Scheduled presentations:

• Predicting the Evolution of Orientation Dependent Damage Caused by Voids Using Deep Learning
  *D. Montes de Oca Zapiain (Sandia National Laboratories), N. Aragon (Sandia National Laboratories), H. Lim (Sandia National Laboratories)
• Data Reduction with Low-Rank Tensor Decompositions that Preserve Scientific Quantities of Interest
  D. Dunlavy (Sandia National Laboratories), E. Phipps (Sandia National Laboratories), *H. Kolla (Sandia National Laboratories), R. Murray (Sandia National Laboratories), J. Shadid (Sandia National Laboratories), E. Phillips (Sandia National Laboratories)
• Nonlinear data compression via image registration
  *R. Van Heyningen (Sandia National Laboratories), P. Blonigan (Sandia National Laboratories), D. Ridzal (Sandia National Laboratories), P. Bochev (Sandia National Laboratories)
• AI-Driven Density-Based Clustering for Large-Scale GPS Data Analysis
  *E. Chehoudi (UQAT)
• Towards the Construction of Inverse Triangular Transport Maps from Federated Multifidelity Information
  *O. Davis (Sandia National Laboratories), G. Geraci (Sandia National Laboratories)
• Dimension Reduction from Shapes as Subspaces using Subspaces of Shapes
  *Z. Grey (NIST)