Steven Young Research Scientist Contact YOUNGSR@ORNL.GOV All Publications Fine-Grained Exploitation of Mixed Precision for Faster CNN Training... Reinforcement Learning-based Traffic Control to Optimize Energy Usage and Throughput (CRADA report) Self-Taught Waveform Synthesis and Analysis in the Amplify-and-Forward Relay Channel Deep Learning for Vertex Reconstruction of Neutrino-nucleus Interaction Events with Combined Energy and Time Data Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINER v A experiment 167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation Unsupervised Identification of Study Descriptors in Toxicology Research: An Experimental Study Deepmod: An Over-the-Air Trainable Machine Modem for Resilient PHY Layer Communications A Study of Complex Deep Learning Networks on High-Performance, Neuromorphic, and Quantum Computers Neural Networks and Graph Algorithms with Next-Generation Processors... Adiabatic Quantum Computation Applied to Deep Learning Networks DeepPDF: A Deep Learning Approach to Extracting Text from PDFs Neuromorphic computing for temporal scientific data classification Data mining for better material synthesis: The case of pulsed laser deposition of complex oxides Optimizing Convolutional Neural Networks for Cloud Detection Vertex reconstruction of neutrino interactions using deep learning A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers... An analysis of image storage systems for scalable training of deep neural networks Optimizing deep learning hyper-parameters through an evolutionary algorithm Pagination First page « First Previous page ‹â¶Ä¹ Page 1 Current page 2 Key Links Organizations Computing and Computational Sciences Directorate Computer Science and Mathematics Division Data and AI Systems Section Learning Systems Group
