Travis Johnston

Oak Ridge National Laboratory — United States

Mathematics · Physical Sciences

12h-index477citations44works0.02yr avg
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Research Topics

Limits and Structures in Graph Theory(8), Machine Learning in Materials Science(7), Advanced Neural Network Applications(6), Advanced Graph Theory Research(6), Machine Learning and Data Classification(6)

Publications44 total

HPC Analytics of Fused Thermal Plants Data to Optimize Operating Envelope
2022Open Access
Structure Prediction from Scattering Profiles: A Neutron-Scattering Use-Case
2022· 1 cited
High frequency accuracy and loss data of random neural networks trained on image datasets
Data in Brief·2022· 5 citedOpen Access
Building High-throughput Neural Architecture Search Workflows via a Decoupled Fitness Prediction Engine
IEEE Transactions on Parallel and Distributed Systems·2022· 6 citedOpen Access
Co-design Center for Exascale Machine Learning Technologies (ExaLearn)
The International Journal of High Performance Computing Applications·2021· 14 citedOpen Access
DeepMerge – II. Building robust deep learning algorithms for merging galaxy identification across domains
Monthly Notices of the Royal Astronomical Society·2021· 44 citedOpen Access
Data Fusion: A Project Update & Pathway Forward
2021
Architecture Descriptions and High Frequency Accuracy and Loss Data of Random Neural Networks Trained on Image Datasets
Harvard Dataverse·2021· 1 citedOpen Access
PEng4NN: An Accurate Performance Estimation Engine for Efficient Automated Neural Network Architecture Search
arXiv (Cornell University)·2021Open Access
Domain Adaptation for Cross-Domain Studies of Merging Galaxies
2021Open Access
Structure Prediction from Neutron Scattering Profiles: A Data Sciences Approach
2020· 3 citedOpen Access
Domain adaptation techniques for improved cross-domain study of galaxy mergers
arXiv (Cornell University)·2020· 5 citedOpen Access
Deep Reinforcement Learning for Residential HVAC Control with Consideration of Human Occupancy
2020· 10 citedOpen Access
Classifying and analyzing small-angle scattering data using weighted<i>k</i>nearest neighbors machine learning techniques
Journal of Applied Crystallography·2020· 42 citedOpen Access
A survey of algorithms for transforming molecular dynamics data into metadata for <i>in situ</i> analytics based on machine learning methods
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences·2020· 13 citedOpen Access
Exascale Deep Learning to Accelerate Cancer Research
2019· 4 citedOpen Access
Learning to Predict Material Structure from Neutron Scattering Data
2019· 19 citedOpen Access
Multi-Objective Optimization for Size and Resilience of Spiking Neural Networks
2019· 1 citedOpen Access
A Novel Pruning Method for Convolutional Neural Networks Based off Identifying Critical Filters
Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning)·2019· 2 citedOpen Access
Creating a portable, high-level graph analytics paradigm for compute and data-intensive applications
International Journal of High Performance Computing and Networking·2018· 2 citedOpen Access
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Frequent Co-authors

Michela Taufer(14), Steven R. Young(5), Thomas E. Potok(4), Robert M. Patton(4), Gabriel Perdue(4), Cristina García–Cardona(4), Ramakrishnan Kannan(4), Thomas Proffen(4), Sudip K. Seal(4), Linyuan Lü(4), Ariel Keller Rorabaugh(4), Silvina Caíno‐Lores(4), Derek Rose(3), Aleksandra Ćiprijanović(3), Diana Kafkes(3), Kathryn Downey(3), Sydney Jenkins(3), Sandeep Madireddy(3), B. Nord(3), Catherine D. Schuman(3)