OCTOBER 24, 2023 Report Increased Interpretability for Model-Driven Deception: MARS LDRD Project ( Read More )
OCTOBER 18, 2023 Conference Paper Developing a Composite Vacuum Insulated Panel (VIP) Insulation/Vinyl Siding Composite Technology for Retrofitting Residential Walls ( Read More )
OCTOBER 13, 2023 Journal Article Multifidelity Deep Operator Networks For Data-Driven and Physics-Informed Problems ( Read More )
OCTOBER 13, 2023 Journal Article Disaster Risk and Artificial Intelligence: A Framework to Characterize Conceptual Synergies and Future Opportunities ( Read More )
OCTOBER 13, 2023 Conference Paper TopFusion: Using Topological Feature Space for Fusion and Imputation in Multi-Modal Data ( Read More )
OCTOBER 13, 2023 Conference Paper Auto-HPCnet: An Automatic Framework to Build Neural Network-based Surrogate for High-Performance Computing Applications ( Read More )
OCTOBER 11, 2023 Journal Article On the dual advantage of placing observations through forward sensitivity analysis ( Read More )
OCTOBER 11, 2023 Journal Article Evaluation of SNOLAB background mitigation procedures through the use of an ICP-MS based dust monitoring methodology ( Read More )
OCTOBER 5, 2023 Journal Article Identification of Voltage Stability Critical Locations for Future Large Grids with High Renewable Mix ( Read More )
SEPTEMBER 22, 2023 Journal Article Global nitrogen deposition inputs to cropland at national scale from 1961 to 2020 ( Read More )
SEPTEMBER 20, 2023 Conference Paper TopTemp: Parsing Precipitate Structure from Temper Topology ( Read More )
SEPTEMBER 16, 2023 Journal Article On the statistical theory of self-gravitating collisionless flow ( Read More )
SEPTEMBER 12, 2023 Journal Article Computational studies of impurity migration during induction stirring of molten uranium ( Read More )
SEPTEMBER 7, 2023 Conference Paper Experimental Observations of the Topology of Convolutional Neural Network Activations ( Read More )
SEPTEMBER 7, 2023 Conference Paper Quantifying the robustness of deep multispectral segmentation models against natural perturbations and data poisoning ( Read More )