Travis Johnston
Title
Cited by
Cited by
Year
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
352017
Vibrational properties of ferroelectric β-vinylidene fluoride polymers and oligomers
SM Nakhmanson, R Korlacki, JT Johnston, S Ducharme, Z Ge, JM Takacs
Physical Review B 81 (17), 174120, 2010
322010
Turán Problems on Non-Uniform Hypergraphs
JT Johnston, L Lu
Electronic Journal of Combinatorics 21 (4), 34, 2014
212014
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
202018
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
132015
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
102017
Performance tuning of mapreduce jobs using surrogate-based modeling
T Johnston, M Alsulmi, P Cicotti, M Taufer
Procedia Computer Science 51, 49-59, 2015
102015
Abelian groups yield many large families for the diamond problem
É Czabarka, A Dutle, T Johnston, LA Székely
European Journal of Mathematics 1 (2), 320-328, 2015
92015
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
82017
Boolean algebras and Lubell functions
T Johnston, L Lu, KG Milans
Journal of Combinatorial Theory, Series A 136, 174-183, 2015
82015
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
72019
Oligo (vinylidene fluoride) Langmuir-Blodgett films studied by spectroscopic ellipsometry and the density functional theory
R Korlacki, JT Johnson, J Kim, S Ducharme, DW Thompson, VM Fridkin, ...
The Journal of chemical physics 129 (6), 064704, 2008
72008
Strong jumps and Lagrangians of non-uniform hypergraphs
T Johnston, L Lu
arXiv preprint arXiv:1403.1220, 2014
62014
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
ASHRAE Transactions 126 (1), 2020
52020
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
52019
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
52019
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), 2020
42020
Early experiences on Summit: Data analytics and AI applications
DE Womble, M Shankar, W Joubert, JT Johnston, JC Wells, JA Nichols
IBM Journal of Research and Development 63 (6), 2: 1-2: 9, 2019
32019
Hyppo: A hybrid, piecewise polynomial modeling technique for non-smooth surfaces
T Johnston, C Zanin, M Taufer
2016 28th International Symposium on Computer Architecture and High …, 2016
32016
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
22019
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Articles 1–20