DeepMerge–II. Building robust deep learning algorithms for merging galaxy identification across domains A Ćiprijanović, D Kafkes, K Downey, S Jenkins, GN Perdue, S Madireddy, ...
Monthly Notices of the Royal Astronomical Society 506 (1), 677-691, 2021
55 2021 Evolving Deep Networks Using HPC SR Young, DC Rose, T Johnston, WT Heller, TP Karnowski, TE Potok, ...
MLHPC'17 Proceedings of the Machine Learning on HPC Environments, 7, 2017
52 2017 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 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
39 2020 Vibrational properties of ferroelectric SM Nakhmanson, R Korlacki, JT Johnston, S Ducharme, Z Ge, JM Takacs
Physical Review B—Condensed Matter and Materials Physics 81 (17), 174120, 2010
36 2010 Resilience and robustness of spiking neural networks for neuromorphic systems CD Schuman, JP Mitchell, JT Johnston, M Parsa, B Kay, P Date, ...
2020 International Joint Conference on Neural Networks (IJCNN), 1-10, 2020
27 2020 Optimizing Convolutional Neural Networks for Cloud Detection T Johnston, SR Young, D Hughes, RM Patton, D White
MLHPC'17 Proceedings of the Machine Learning on HPC Environments, 9 pages, 2017
26 2017 Laparoscopic surgical skills are significantly improved by the use of a portable laparoscopic simulator: results of a randomized controlled trial TJ Johnston, B Tang, A Alijani, I Tait, RJ Steele, J Ker, G Nabi, ...
World journal of surgery 37 (5), 957-964, 2013
25 2013 Learning to predict material structure from neutron scattering data C Garcia-Cardona, R Kannan, T Johnston, T Proffen, K Page, SK Seal
2019 IEEE International Conference on Big Data (Big Data), 4490-4497, 2019
24 2019 Turán Problems on Non-Uniform Hypergraphs JT Johnston, L Lu
Electronic Journal of Combinatorics 21 (4), 34, 2014
24 2014 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 In situ data analytics and indexing of protein trajectories T Johnston, B Zhang, A Liwo, S Crivelli, M Taufer
Journal of computational chemistry 38 (16), 1419-1430, 2017
20 2017 On the need for reproducible numerical accuracy through intelligent runtime selection of reduction algorithms at the extreme scale D Chapp, T Johnston, M Taufer
2015 IEEE International Conference on Cluster Computing, 166-175, 2015
19 2015 Co-design center for exascale machine learning technologies (exalearn) FJ Alexander, J Ang, JA Bilbrey, J Balewski, T Casey, R Chard, J Choi, ...
The International Journal of High Performance Computing Applications 35 (6 …, 2021
18 2021 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
16 2019 Low size, weight, and power neuromorphic computing to improve combustion engine efficiency CD Schuman, SR Young, JP Mitchell, JT Johnston, D Rose, ...
2020 11th International Green and Sustainable Computing Workshops (IGSC), 1-8, 2020
15 2020 Rl-hems: Reinforcement learning based home energy management system for hvac energy optimization O Kotevska, K Kurte, J Munk, T Johnston, E Mckee, K Perumalla, H Zandi
Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States), 2020
15 2020 Multi-objective optimization for size and resilience of spiking neural networks M Dimovska, T Johnston, CD Schuman, JP Mitchell, TE Potok
2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile …, 2019
13 2019 Boolean algebras and Lubell functions T Johnston, L Lu, KG Milans
Journal of Combinatorial Theory, Series A 136, 174-183, 2015
11 2015 Performance tuning of MapReduce jobs using surrogate-based modeling T Johnston, M Alsulmi, P Cicotti, M Taufer
Procedia Computer Science 51, 49-59, 2015
11 2015 
Michela TauferJack Dongarra Professor in High Performance Computing, The University of TennesseeEmail verificata su acm.org
