AUGUST 13, 2023 Journal Article Elastic Resource Management for Deep Learning Applications in a Container Cluster ( Read More )
AUGUST 13, 2023 Conference Paper Do Neural Networks Trained with Topological Features Learn Different Internal Representations? ( Read More )
JULY 12, 2023 Journal Article COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms ( Read More )
JULY 11, 2023 Journal Article Constructing Neural Network-Based Models for Simulating Dynamical Systems ( Read More )
JULY 11, 2023 Journal Article Multi-Level Optimization with the Koopman Operator for Data-Driven, Domain-Aware, and Dynamic System Security ( Read More )
JULY 11, 2023 Conference Paper FPGA Acceleration of GCN in Light of the Symmetry of Graph Adjacency Matrix ( Read More )
JULY 11, 2023 Journal Article Dynamic Network Analysis of Nuclear Science Literature for Research Influence Assessment ( Read More )
JULY 11, 2023 Report Building a better framework for evaluating human well-being impacts in global change analysis: The example of energy security ( Read More )
JULY 8, 2023 Conference Paper AMG Preconditioners based on parallel hybrid coarsening and multi-objective graph matching ( Read More )
JULY 7, 2023 Conference Paper Software-Hardware Co-design of Heterogeneous SmartNIC System for Recommendation Models Inference and Training ( Read More )
JUNE 30, 2023 Journal Article A Multifidelity Deep Operator Network Approach to Closure for Multiscale Systems ( Read More )
JUNE 21, 2023 Report Fixing Amdahl's Law within the Limits of Accelerated Systems: FALLACY ( Read More )
JUNE 9, 2023 Journal Article Physics-informed machine-learning model of temperature evolution under solid phase processes ( Read More )
MAY 26, 2023 Journal Article A Bayesian Approach for Characterizing and Mitigating Gate and Measurement Errors ( Read More )
MAY 10, 2023 Conference Paper Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operationson Spatial Accelerators ( Read More )
MAY 5, 2023 Journal Article Physics-informed Karhunen-Loeve and Neural Network Approximations for Solving Inverse Differential Equation Problems ( Read More )