| Optimizing Deep Learning Hyper-parameters Through an Evolutionary Algorithm SR Young, DC Rose, TP Karnowski, SH Lim, RM Patton Proceedings of the Workshop on Machine Learning in High-Performance …, 2015 | 561 | 2015 |
| A 1 TOPS/W Analog Deep Machine-Learning Engine With Floating-Gate Storage in 0.13 µm CMOS J Lu, S Young, I Arel, Holleman, J. IEEE Journal of Solid-State Circuits 50 (1), 270-281, 2015 | 179 | 2015 |
| A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers TE Potok, CD Schuman, SR Young, RM Patton, F Spedalieri, J Liu, ... Proceedings of the Workshop on Machine Learning in High Performance …, 2016 | 118 | 2016 |
| A Fast and Stable Incremental Clustering Algorithm S Young, I Arel, T Karnowski, D Rose Information Technology: New Generations (ITNG), 2010 Seventh International …, 2010 | 79 | 2010 |
| Evolving Deep Networks Using HPC SR Young, DC Rose, T Johnston, WT Heller, TP Karnowski, TE Potok, ... Proceedings of the 3rd Workshop on Machine Learning in HPC Environments, 2017 | 54 | 2017 |
| Data mining for better material synthesis: The case of pulsed laser deposition of complex oxides SR Young, A Maksov, M Ziatdinov, Y Cao, M Burch, J Balachandran, L Li, ... Journal of Applied Physics 123 (11), 2018 | 44 | 2018 |
| Adiabatic Quantum Computation Applied to Deep Learning Networks J Liu, FM Spedalieri, KT Yao, TE Potok, C Schuman, S Young, R Patton, ... Entropy 20 (5), 380, 2018 | 43 | 2018 |
| Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINERvA experiment GN Perdue, A Ghosh, M Wospakrik, F Akbar, DA Andrade, M Ascencio, ... Journal of Instrumentation 13 (11), P11020, 2018 | 42 | 2018 |
| Classifying and analyzing small-angle scattering data using weighted k nearest neighbors machine learning techniques RK Archibald, M Doucet, T Johnston, SR Young, E Yang, WT Heller Journal of Applied Crystallography 53 (2), 326-334, 2020 | 41 | 2020 |
| 167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation RM Patton, JT Johnston, SR Young, CD Schuman, DD March, TE Potok, ... Proceedings of the International Conference for High Performance Computing …, 2018 | 40 | 2018 |
| Accelerating Scientific Computing in the Post-Moore’s Era KE Hamilton, CD Schuman, SR Young, RS Bennink, N Imam, TS Humble ACM Transactions on Parallel Computing (TOPC) 7 (1), 1-31, 2020 | 29 | 2020 |
| Optimizing Convolutional Neural Networks for Cloud Detection T Johnston, SR Young, D Hughes, RM Patton, D White Proceedings of the 3rd Workshop on Machine Learning in HPC Environments, 4, 2017 | 27 | 2017 |
| Exascale Deep Learning to Accelerate Cancer Research RM Patton, JT Johnston, SR Young, CD Schuman, TE Potok, DC Rose, ... 2019 IEEE International Conference on Big Data (Big Data), 1488-1496, 2019 | 22 | 2019 |
| An Analysis of Image Storage Systems for Scalable Training of Deep Neural Networks SH Lim, SR Young, RM Patton The Seventh workshop on Big Data Benchmarks, Performance Optimization, and …, 2016 | 20 | 2016 |
| Neural Networks and Graph Algorithms with Next-Generation Processors KE Hamilton, CD Schuman, SR Young, N Imam, TS Humble 2018 IEEE International Parallel and Distributed Processing Symposium …, 2018 | 19 | 2018 |
| Deeppdf: A deep learning approach to extracting text from pdfs C Stahl, S Young, D Herrmannova, R Patton, J Wells Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States), 2018 | 18 | 2018 |
| Vertex reconstruction of neutrino interactions using deep learning AM Terwilliger, GN Perdue, D Isele, RM Patton, SR Young 2017 International Joint Conference on Neural Networks (IJCNN), 2275-2281, 2017 | 18 | 2017 |
| Ensembles of Networks Produced from Neural Architecture Search EJ Herron, SR Young, TE Potok International Conference on High Performance Computing, 223-234, 2020 | 17 | 2020 |
| Evolving Energy Efficient Convolutional Neural Networks SR Young, P Devineni, M Parsa, JT Johnston, B Kay, RM Patton, ... 2019 IEEE International Conference on Big Data (Big Data), 4479-4485, 2019 | 17 | 2019 |
| Neuromorphic computing for temporal scientific data classification CD Schuman, TE Potok, S Young, R Patton, G Perdue, G Chakma, ... Proceedings of the Neuromorphic Computing Symposium, 2, 2017 | 17 | 2017 |
Derek RoseR&D Associate, Oak Ridge National LaboratoryZweryfikowany adres z ornl.gov
