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Department of Energy (DOE)
Highlights
The Minos Computing Library: efficient parallel programming for extremely heterogeneous systems
In-Depth Optimization with the OpenACC-to-FPGA Framework on an Arria 10 FPGA
Estimating Lossy Compressibility of Scientific Data Using Deep Neural Networks
Improving In Transit and In Situ Analysis and Visualization
3D Coded SUMMA: Communication-Efficient and Robust Parallel Matrix Multiplication
Designing Error Inhibiting Schemes with Post-Processing Capabilities
ORNL researchers develop fast, implicit solvers for multiscale kinetic equations of charged particle transport
A model order reduction method for non-classical models of diffusion
XACC: A System-level Software Infrastructure for Heterogeneous Quantum-Classical Computing
ASCENDS: Advanced data SCiENce toolkit for Non-Data Scientists
Adversarial Training for Privacy-Preserving Deep Learning Model Distribution
Automatic Extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks
Evolving Energy Efficient Convolutional Neural Networks
Self-stabilizing Connected Components
RevNet-based level-set learning for dimensionality reduction in predicting complex systems
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