Massimiliano Lupo Pasini Data Scientist Contact LUPOPASINIM@ORNL.GOV All Publications Stable parallel training of Wasserstein conditional generative adversarial neural networks Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems Fast and Accurate Predictions of Total Energy for Solid Solution Alloys with Graph Convolutional Neural Networks Anderson Acceleration for Distributed Training of Deep Learning Models... Hierarchical Model Reduction Driven by a Proper Orthogonal Decomposition for Parametrized Advection-Diffusion-Reaction Problems Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks : *Full/Regular Research Paper submission for the symposium CSCI-ISAI: Artificial Intelligence Scalable balanced training of conditional generative adversarial neural networks on image data A scalable algorithm for the optimization of neural network architectures Fast and stable deep-learning predictions of material properties for solid solution alloys Benchmark of the LAMMPS code on CRESCO and SUMMIT HPC systems A Parallel Strategy for Density Functional Theory Computations on Accelerated Nodes... Convergence analysis of Anderson‐type acceleration of Richardson's iteration Pagination First page « First Previous page ‹Ĺ Page 1 Current page 2 Key Links Curriculum Vitae Organizations Computing and Computational Sciences Directorate Computational Sciences and Engineering Division Advanced Computing Methods for Engineered Systems Section Computational Coupled Physics
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