Robert M. Patton

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 53

Top Topics

Diabetic Retinopathy

Document Relevance

Top Venues

Publications

Mark Coletti, Chathika Gunaratne, Steven R. Young, Swetha Varadarajan, Robert M. Patton, Thomas E. Potok
Efficacy of using a dynamic length representation vs. a fixed-length for neuroarchitecture search. GECCO Companion (2024)
Prasanna Date, Chathika Gunaratne, Shruti R. Kulkarni, Robert M. Patton, Mark Coletti, Thomas E. Potok
SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing. ICONS (2023)
Prasanna Date, Chathika Gunaratne, Shruti Kulkarni, Robert M. Patton, Mark Coletti, Thomas E. Potok
SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing. CoRR (2023)
Ramakrishnan Kannan, Piyush Sao, Hao Lu, Jakub Kurzak, Gundolf Schenk, Yongmei Shi, Seung-Hwan Lim, Sharat Israni, Vijay Thakkar, Guojing Cong, Robert M. Patton, Sergio E. Baranzini, Richard W. Vuduc, Thomas E. Potok
Exaflops Biomedical Knowledge Graph Analytics. SC (2022)
Catherine D. Schuman, James S. Plank, Robert M. Patton, Thomas E. Potok, Garrett S. Rose
A Framework to Enable Top-Down Co-Design of Neuromorphic Systems for Real-World Applications. NICE (2022)
Mark Coletti, Chathika Gunaratne, Catherine D. Schuman, Robert M. Patton
Training reinforcement learning models via an adversarial evolutionary algorithm. ICPP Workshops (2022)
Chathika Gunaratne, Robert M. Patton
Genetic programming for understanding cognitive biases that generate polarization in social networks. GECCO Companion (2022)
Catherine D. Schuman, Robert M. Patton, Shruti R. Kulkarni, Maryam Parsa, Christopher G. Stahl, Nicholas Quentin Haas, J. Parker Mitchell, Shay Snyder, Amelie Nagle, Alexandra Shanafield, Thomas E. Potok
Evolutionary vs imitation learning for neuromorphic control at the edge. Neuromorph. Comput. Eng. 2 (1) (2022)
Robert M. Patton, Prasanna Date, Shruti R. Kulkarni, Chathika Gunaratne, Seung-Hwan Lim, Guojing Cong, Steven R. Young, Mark Coletti, Thomas E. Potok, Catherine D. Schuman
Neuromorphic Computing for Scientific Applications. RSDHA@SC (2022)
Mark A. Coletti, Shang Gao, Spencer Paulissen, Nicholas Quentin Haas, Robert M. Patton
Diagnosing autonomous vehicle driving criteria with an adversarial evolutionary algorithm. GECCO Companion (2021)
James S. Plank, Catherine D. Schuman, Robert M. Patton
An Oracle and Observations for the OpenAI Gym / ALE Freeway Environment. CoRR (2021)
Seung-Hwan Lim, Junghoon Chae, Guojing Cong, Drahomira Herrmannova, Robert M. Patton, Ramakrishnan Kannan, Thomas E. Potok
Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis. IEEE BigData (2021)
Prasanna Date, Bill Kay, Catherine D. Schuman, Robert M. Patton, Thomas E. Potok
Computational Complexity of Neuromorphic Algorithms. ICONS (2021)
Robert M. Patton, Catherine D. Schuman, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Nicholas Quentin Haas, Christopher G. Stahl, Spencer Paulissen, Prasanna Date, Thomas E. Potok, Shay Sneider
Neuromorphic Computing for Autonomous Racing. ICONS (2021)
Drahomira Herrmannova, Chathika Gunaratne, Vickie Walker, Andrew Rooney, Robert M. Patton, Mary Wolfe, Charles Schmitt
Weak Supervision for Scientific Document Relevance Tagging. JCDL (2021)
Tirthankar Ghosal, Piyush Tiwary, Robert M. Patton, Christopher G. Stahl
Towards establishing a research lineage via identification of significant citations. Quant. Sci. Stud. 2 (4) (2021)
Shang Gao, Spencer Paulissen, Mark Coletti, Robert M. Patton
Quantitative Evaluation of Autonomous Driving in CARLA. IV Workshops (2021)
Hui Guan, Laxmikant Kishor Mokadam, Xipeng Shen, Seung-Hwan Lim, Robert M. Patton
FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks. MLSys (2020)
J. Parker Mitchell, Catherine D. Schuman, Robert M. Patton, Thomas E. Potok
Caspian: A Neuromorphic Development Platform. NICE (2020)
Catherine D. Schuman, J. Parker Mitchell, Robert M. Patton, Thomas E. Potok, James S. Plank
Evolutionary Optimization for Neuromorphic Systems. NICE (2020)
Catherine D. Schuman, J. Parker Mitchell, J. Travis Johnston, Maryam Parsa, Bill Kay, Prasanna Date, Robert M. Patton
Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems. IJCNN (2020)
Catherine D. Schuman, J. Parker Mitchell, Maryam Parsa, James S. Plank, Samuel D. Brown, Garrett S. Rose, Robert M. Patton, Thomas E. Potok
Automated Design of Neuromorphic Networks for Scientific Applications at the Edge. IJCNN (2020)
Ramakrishnan Kannan, Piyush Sao, Hao Lu, Drahomira Herrmannova, Vijay Thakkar, Robert M. Patton, Richard W. Vuduc, Thomas E. Potok
Scalable knowledge graph analytics at 136 petaflop/s. SC (2020)
Prasanna Date, Robert M. Patton, Catherine D. Schuman, Thomas E. Potok
Efficiently embedding QUBO problems on adiabatic quantum computers. Quantum Inf. Process. 18 (4) (2019)
Robert M. Patton, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou
Exascale Deep Learning to Accelerate Cancer Research. IEEE BigData (2019)
Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz
Exascale Deep Learning to Accelerate Cancer Research. CoRR (2019)
Catherine D. Schuman, James S. Plank, Robert M. Patton, Thomas E. Potok
Island model for parallel evolutionary optimization of spiking neuromorphic computing. GECCO (Companion) (2019)
Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman, Robert M. Patton, Thomas E. Potok, Kaushik Roy
Bayesian-based Hyperparameter Optimization for Spiking Neuromorphic Systems. IEEE BigData (2019)
Jeremy T. Johnston, Steven R. Young, Catherine D. Schuman, Junghoon Chae, Don D. March, Robert M. Patton, Thomas E. Potok
Fine-Grained Exploitation of Mixed Precision for Faster CNN Training. MLHPC@SC (2019)
Steven R. Young, Pravallika Devineni, Maryam Parsa, J. Travis Johnston, Bill Kay, Robert M. Patton, Catherine D. Schuman, Derek C. Rose, Thomas E. Potok
Evolving Energy Efficient Convolutional Neural Networks. IEEE BigData (2019)
Junghoon Chae, Catherine D. Schuman, Steven R. Young, J. Travis Johnston, Derek C. Rose, Robert M. Patton, Thomas E. Potok
Visualization System for Evolutionary Neural Networks for Deep Learning. IEEE BigData (2019)
Drahomira Herrmannova, Petr Knoth, Christopher G. Stahl, Robert M. Patton, Jack C. Wells
Research Collaboration Analysis Using Text and Graph Features. CICLing (2) (2018)
Drahomira Herrmannova, Steven Robert Young, Robert M. Patton, Christopher G. Stahl, Nicole C. Kleinstreuer, Mary S. Wolfe
Unsupervised Identification of Study Descriptors in Toxicology Research: An Experimental Study. Louhi@EMNLP (2018)
Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Don D. March, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Thomas P. Karnowski, Maxim A. Ziatdinov, Sergei V. Kalinin
167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation. SC (2018)
Thomas E. Potok, Catherine D. Schuman, Steven R. Young, Robert M. Patton, Federico M. Spedalieri, Jeremy Liu, Ke-Thia Yao, Garrett S. Rose, Gangotree Chakma
A Study of Complex Deep Learning Networks on High-Performance, Neuromorphic, and Quantum Computers. ACM J. Emerg. Technol. Comput. Syst. 14 (2) (2018)
Drahomira Herrmannova, Petr Knoth, Robert M. Patton
Analyzing Citation-Distance Networks for Evaluating Publication Impact. LREC (2018)
Jeremy Liu, Federico M. Spedalieri, Ke-Thia Yao, Thomas E. Potok, Catherine D. Schuman, Steven R. Young, Robert M. Patton, Garrett S. Rose, Gangotree Chakma
Adiabatic Quantum Computation Applied to Deep Learning Networks. Entropy 20 (5) (2018)
Drahomira Herrmannova, Steven R. Young, Robert M. Patton, Christopher G. Stahl, Nicole C. Kleinstreuer, Mary S. Wolfe
Unsupervised Identification of Study Descriptors in Toxicology Research: An Experimental Study. CoRR (2018)
Randall Pittman, Hui Guan, Xipeng Shen, Seung-Hwan Lim, Robert M. Patton
Exploring flexible communications for streamlining DNN ensemble training pipelines. SC (2018)
Drahomira Herrmannova, Robert M. Patton, Petr Knoth, Christopher G. Stahl
Do citations and readership identify seminal publications? Scientometrics 115 (1) (2018)
Drahomira Herrmannova, Robert M. Patton, Petr Knoth, Christopher G. Stahl
Do Citations and Readership Identify Seminal Publications? CoRR (2018)
Adam M. Terwilliger, Gabriel N. Perdue, David Isele, Robert M. Patton, Steven R. Young
Vertex reconstruction of neutrino interactions using deep learning. IJCNN (2017)
Thomas E. Potok, Catherine D. Schuman, Steven R. Young, Robert M. Patton, Federico M. Spedalieri, Jeremy Liu, Ke-Thia Yao, Garrett S. Rose, Gangotree Chakma
A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers. CoRR (2017)
Steven R. Young, Derek C. Rose, J. Travis Johnston, William T. Heller, Thomas P. Karnowski, Thomas E. Potok, Robert M. Patton, Gabriel N. Perdue, Jonathan A. Miller
Evolving Deep Networks Using HPC. MLHPC@SC (2017)
Robert M. Patton, Thomas E. Potok, Petr Knoth, Drahomira Herrmannova
Workshop on Scholarly Web Mining (SWM 2017). WSDM (2017)
Robert M. Patton, Drahomira Herrmannova, Christopher G. Stahl, Jack C. Wells, Thomas E. Potok
Audience Based View of Publication Impact. WOSP@JCDL (2017)
Catherine D. Schuman, Thomas E. Potok, Steven R. Young, Robert M. Patton, Gabriel N. Perdue, Gangotree Chakma, Austin Wyer, Garrett S. Rose
Neuromorphic computing for temporal scientific data classification. NCS (2017)
J. Travis Johnston, Steven R. Young, David Hughes, Robert M. Patton, Devin White
Optimizing Convolutional Neural Networks for Cloud Detection. MLHPC@SC (2017)
Catherine D. Schuman, Thomas E. Potok, Robert M. Patton, J. Douglas Birdwell, Mark E. Dean, Garrett S. Rose, James S. Plank
A Survey of Neuromorphic Computing and Neural Networks in Hardware. CoRR (2017)
Drahomira Herrmannova, Robert M. Patton, Petr Knoth, Christopher G. Stahl
Citations and Readership are Poor Indicators of Research Excellence: Introducing TrueImpactDataset, a New Dataset for Validating Research Evaluation Metrics. SWM@WSDM (2017)
Stephen L. Smith, Stefano Cagnoni, Robert M. Patton
MedGEC'16 Chairs' Welcome. GECCO (Companion) (2016)
Thomas E. Potok, Catherine D. Schuman, Steven R. Young, Robert M. Patton, Federico M. Spedalieri, Jeremy Liu, Ke-Thia Yao, Garrett S. Rose, Gangotree Chakma
A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers. MLHPC@SC (2016)
Robert M. Patton, Christopher G. Stahl, Jack C. Wells
Measuring Scientific Impact Beyond Citation Counts. D Lib Mag. 22 (9/10) (2016)
Steven R. Young, Derek C. Rose, Thomas P. Karnowski, Seung-Hwan Lim, Robert M. Patton
Optimizing deep learning hyper-parameters through an evolutionary algorithm. MLHPC@SC (2015)
Katherine Senter, Sreenivas R. Sukumar, Robert M. Patton, Edward Chaum
Using clinical data, hypothesis generation tools and PubMed trends to discover the association between diabetic retinopathy and antihypertensive drugs. IEEE BigData (2015)
Paul Logasa Bogen, Christopher T. Symons, Amber McKenzie, Robert M. Patton, Robert E. Gillen
Massively scalable near duplicate detection in streams of documents using MDSH. IEEE BigData (2013)
Robert M. Patton, Christopher G. Stahl, Jayson B. Hines, Thomas E. Potok, Jack C. Wells
Multi-year Content Analysis of User Facility Related Publications. D Lib Mag. 19 (9/10) (2013)
Robert M. Patton, Chad A. Steed, Christopher G. Stahl, Jim N. Treadwell
Observing Community Resiliency in Social Media. ICCSA (5) (2013)
Robert M. Patton, Christopher G. Stahl, Thomas E. Potok, Jack C. Wells
Identification of User Facility Related Publications. D Lib Mag. 18 (7/8) (2012)
Robert M. Patton, Wade McNair, Christopher T. Symons, Jim N. Treadwell, Thomas E. Potok
A Text Analysis Approach to Motivate Knowledge Sharing via Microsoft SharePoint. HICSS (2012)
Carlos C. Rojas, Robert M. Patton, Barbara G. Beckerman
Characterizing Mammography Reports for Health Analytics. J. Medical Syst. 35 (5) (2011)
Justin M. Beaver, Robert M. Patton, Thomas E. Potok
An approach to the automated determination of host information value. CICS (2011)
Robert M. Patton, Justin M. Beaver, Thomas E. Potok
Classification of Distributed Data Using Topic Modeling and Maximum Variation Sampling. HICSS (2011)
Robert M. Patton, Justin M. Beaver, Chad A. Steed, Thomas E. Potok, Jim N. Treadwell
Hierarchical clustering and visualization of aggregate cyber data. IWCMC (2011)
Robert M. Patton, Carlos C. Rojas, Barbara G. Beckerman, Thomas E. Potok
A Computational Framework for Search, Discovery, and Trending of Patient Health in Radiology Reports. HISB (2011)
Carlos C. Rojas, Robert M. Patton, Barbara G. Beckerman
Characterizing mammography reports for health analytics. IHI (2010)
Robert M. Patton, Barbara G. Beckerman, Thomas E. Potok, Jim N. Treadwell
Genetic algorithm for analysis of abdominal aortic aneurysms in radiology reports. GECCO (Companion) (2010)
Laura L. Pullum, Christopher T. Symons, Robert M. Patton, Barbara G. Beckerman
Architecture-level dependability analysis of a medical decision support system. SEHC@ICSE (2010)
Robert M. Patton, Thomas E. Potok
Discovering Potential Precursors of Mammography Abnormalities Based on Textual Features, Frequencies, and Sequences. ICAISC (1) (2010)
Robert M. Patton, Thomas E. Potok, Barbara G. Beckerman, Jim N. Treadwell
A genetic algorithm for learning significant phrase patterns in radiology reports. GECCO (Companion) (2009)
Robert M. Patton, Thomas E. Potok
Identifying Event Impacts by Monitoring the News Media. IV (2008)
Robert M. Patton, Jim N. Treadwell, Ryan A. Kerekes, Thomas E. Potok
Discovery, analysis, and characteristics of event impacts. FUSION (2008)
Robert M. Patton, Barbara G. Beckerman, Thomas E. Potok
Analysis of mammography reports using maximum variation sampling. GECCO (Companion) (2008)
Robert M. Patton, Thomas E. Potok
Discovering event evidence amid massive, dynamic datasets. GECCO (Companion) (2007)
Robert M. Patton, Thomas E. Potok
Characterizing large text corpora using a maximum variation sampling genetic algorithm. GECCO (2006)
Paul J. Palathingal, Thomas E. Potok, Robert M. Patton
Agent Based Approach for Searching, Mining and Managing Enormous Amounts of Spatial Image Data. FLAIRS Conference (2005)
Robert M. Patton, Thomas E. Potok
Adaptive Sampling of Text Documents. IASSE (2004)
Gwendolyn H. Walton, Robert M. Patton, Douglas J. Parsons
Usage testing of military simulation systems. WSC (2001)