Usage testing of military simulation systems. - Gwendolyn H. Walton; Robert M. Patton; Douglas J. Parsons (WSC, 2001)

Adaptive Sampling of Text Documents. - Robert M. Patton; Thomas E. Potok (IASSE, 2004)

Agent Based Approach for Searching, Mining and Managing Enormous Amounts of Spatial Image Data. - Paul J. Palathingal; Thomas E. Potok; Robert M. Patton (FLAIRS, 2005)

Characterizing large text corpora using a maximum variation sampling genetic algorithm. - Robert M. Patton; Thomas E. Potok (GECCO, 2006)

Discovering event evidence amid massive, dynamic datasets. - Robert M. Patton; Thomas E. Potok (GECCO (Companion), 2007)

Flocking-based Document Clustering on the Graphics Processing Unit. - Jesse St. Charles; Thomas E. Potok; Robert M. Patton; Xiaohui Cui (NICSO, 2007)

Particle Swarm Based Collective Searching Model for Adaptive Environment. - Xiaohui Cui; Robert M. Patton; Jim N. Treadwell; Thomas E. Potok (NICSO, 2007)

Discovery, analysis, and characteristics of event impacts. - Robert M. Patton; Jim N. Treadwell; Ryan A. Kerekes; Thomas E. Potok (FUSION, 2008)

Analysis of mammography reports using maximum variation sampling. - Robert M. Patton; Barbara G. Beckerman; Thomas E. Potok (GECCO (Companion), 2008)

Identifying Event Impacts by Monitoring the News Media. - Robert M. Patton; Thomas E. Potok (IV, 2008)

A genetic algorithm for learning significant phrase patterns in radiology reports. - Robert M. Patton; Thomas E. Potok; Barbara G. Beckerman; Jim N. Treadwell (GECCO (Companion), 2009)

Genetic algorithm for analysis of abdominal aortic aneurysms in radiology reports. - Robert M. Patton; Barbara G. Beckerman; Thomas E. Potok; Jim N. Treadwell (GECCO (Companion), 2010)

Discovering Potential Precursors of Mammography Abnormalities Based on Textual Features, Frequencies, and Sequences. - Robert M. Patton; Thomas E. Potok (ICAISC (1), 2010)

Architecture-level dependability analysis of a medical decision support system. - Laura L. Pullum; Christopher T. Symons; Robert M. Patton; Barbara G. Beckerman (SEHC@ICSE, 2010)

Analysis and Classification ofMammography Reports using Maximum Variation Sampling. - Robert M. Patton; Barbara G. Beckerman; Thomas E. Potok (Genetic and Evolutionary Computation: Medical Applications, 2011)

An approach to the automated determination of host information value. - Justin M. Beaver; Robert M. Patton; Thomas E. Potok (CICS, 2011)

Classification of Distributed Data Using Topic Modeling and Maximum Variation Sampling. - Robert M. Patton; Justin M. Beaver; Thomas E. Potok (HICSS, 2011)

A Computational Framework for Search, Discovery, and Trending of Patient Health in Radiology Reports. - Robert M. Patton; Carlos C. Rojas; Barbara G. Beckerman; Thomas E. Potok (HISB, 2011)

Hierarchical clustering and visualization of aggregate cyber data. - Robert M. Patton; Justin M. Beaver; Chad A. Steed; Thomas E. Potok; Jim N. Treadwell (IWCMC, 2011)

Characterizing Mammography Reports for Health Analytics. - Carlos C. Rojas; Robert M. Patton; Barbara G. Beckerman (J. Medical Syst., 2011)

A Text Analysis Approach to Motivate Knowledge Sharing via Microsoft SharePoint. - Robert M. Patton; Wade McNair; Christopher T. Symons; Jim N. Treadwell; Thomas E. Potok (HICSS, 2012)

Identification of User Facility Related Publications. - Robert M. Patton; Christopher G. Stahl; Thomas E. Potok; Jack C. Wells (D Lib Mag., 2012)

Massively scalable near duplicate detection in streams of documents using MDSH. - Paul Logasa Bogen; Christopher T. Symons; Amber McKenzie; Robert M. Patton; Robert E. Gillen (IEEE BigData, 2013)

Observing Community Resiliency in Social Media. - Robert M. Patton; Chad A. Steed; Christopher G. Stahl; Jim N. Treadwell (ICCSA (5), 2013)

Multi-year Content Analysis of User Facility Related Publications. - Robert M. Patton; Christopher G. Stahl; Jayson B. Hines; Thomas E. Potok; Jack C. Wells (D Lib Mag., 2013)

Using clinical data, hypothesis generation tools and PubMed trends to discover the association between diabetic retinopathy and antihypertensive drugs. - Katherine Senter; Sreenivas R. Sukumar 001; Robert M. Patton; Edward Chaum (IEEE BigData, 2015)

Optimizing deep learning hyper-parameters through an evolutionary algorithm. - Steven R. Young; Derek C. Rose; Thomas P. Karnowski; Seung-Hwan Lim; Robert M. Patton (MLHPC@SC, 2015)

MedGEC'16 Chairs' Welcome. - Stephen L. Smith 002; Stefano Cagnoni; Robert M. Patton (GECCO (Companion), 2016)

Measuring Scientific Impact Beyond Citation Counts. - Robert M. Patton; Christopher G. Stahl; Jack C. Wells (D Lib Mag., 2016)

Vertex reconstruction of neutrino interactions using deep learning. - Adam M. Terwilliger; Gabriel N. Perdue; David Isele; Robert M. Patton; Steven R. Young (IJCNN, 2017)

Audience Based View of Publication Impact. - Robert M. Patton; Drahomira Herrmannova; Christopher G. Stahl; Jack C. Wells; Thomas E. Potok (WOSP@JCDL, 2017)

Neuromorphic computing for temporal scientific data classification. - Catherine D. Schuman; Thomas E. Potok; Steven R. Young; Robert M. Patton; Gabriel N. Perdue; Gangotree Chakma; Austin Wyer; Garrett S. Rose (NCS, 2017)

Optimizing Convolutional Neural Networks for Cloud Detection. - J. Travis Johnston; Steven R. Young; David Hughes; Robert M. Patton; Devin White (MLHPC@SC, 2017)

Evolving Deep Networks Using HPC. - 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 (MLHPC@SC, 2017)

Citations and Readership are Poor Indicators of Research Excellence: Introducing TrueImpactDataset, a New Dataset for Validating Research Evaluation Metrics. - Drahomira Herrmannova; Robert M. Patton; Petr Knoth; Christopher G. Stahl (SWM@WSDM, 2017)

Workshop on Scholarly Web Mining (SWM 2017). - Robert M. Patton; Thomas E. Potok; Petr Knoth; Drahomira Herrmannova (WSDM, 2017)

A Survey of Neuromorphic Computing and Neural Networks in Hardware. - Catherine D. Schuman; Thomas E. Potok; Robert M. Patton; J. Douglas Birdwell; Mark E. Dean; Garrett S. Rose; James S. Plank (CoRR, 2017)

Unsupervised Identification of Study Descriptors in Toxicology Research: An Experimental Study. - Drahomira Herrmannova; Steven Robert Young; Robert M. Patton; Christopher G. Stahl; Nicole C. Kleinstreuer; Mary S. Wolfe (Louhi@EMNLP, 2018)

Research Collaboration Analysis Using Text and Graph Features. - Drahomira Herrmannova; Petr Knoth; Christopher G. Stahl; Robert M. Patton; Jack C. Wells (CICLing (2), 2018)

Analyzing Citation-Distance Networks for Evaluating Publication Impact. - Drahomira Herrmannova; Petr Knoth; Robert M. Patton (LREC, 2018)

167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation. - 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 (SC, 2018)

Exploring flexible communications for streamlining DNN ensemble training pipelines. - Randall Pittman; Hui Guan 001; Xipeng Shen; Seung-Hwan Lim; Robert M. Patton (SC, 2018)

Adiabatic Quantum Computation Applied to Deep Learning Networks. - 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 (Entropy, 2018)

A Study of Complex Deep Learning Networks on High-Performance, Neuromorphic, and Quantum Computers. - 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 (ACM J. Emerg. Technol. Comput. Syst., 2018)

Do citations and readership identify seminal publications? - Drahomira Herrmannova; Robert M. Patton; Petr Knoth; Christopher G. Stahl (Scientometrics, 2018)

Visualization System for Evolutionary Neural Networks for Deep Learning. - Junghoon Chae; Catherine D. Schuman; Steven R. Young; J. Travis Johnston; Derek C. Rose; Robert M. Patton; Thomas E. Potok (IEEE BigData, 2019)

Bayesian-based Hyperparameter Optimization for Spiking Neuromorphic Systems. - Maryam Parsa; J. Parker Mitchell; Catherine D. Schuman; Robert M. Patton; Thomas E. Potok; Kaushik Roy 001 (IEEE BigData, 2019)

Exascale Deep Learning to Accelerate Cancer Research. - 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 (IEEE BigData, 2019)

Evolving Energy Efficient Convolutional Neural Networks. - Steven R. Young; Pravallika Devineni; Maryam Parsa; J. Travis Johnston; Bill Kay; Robert M. Patton; Catherine D. Schuman; Derek C. Rose; Thomas E. Potok (IEEE BigData, 2019)

Island model for parallel evolutionary optimization of spiking neuromorphic computing. - Catherine D. Schuman; James S. Plank; Robert M. Patton; Thomas E. Potok (GECCO (Companion), 2019)

Fine-Grained Exploitation of Mixed Precision for Faster CNN Training. - Jeremy T. Johnston; Steven R. Young; Catherine D. Schuman; Junghoon Chae; Don D. March; Robert M. Patton; Thomas E. Potok (MLHPC@SC, 2019)

Efficiently embedding QUBO problems on adiabatic quantum computers. - Prasanna Date; Robert M. Patton; Catherine D. Schuman; Thomas E. Potok (Quantum Inf. Process., 2019)

Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems. - Catherine D. Schuman; J. Parker Mitchell; J. Travis Johnston; Maryam Parsa; Bill Kay; Prasanna Date; Robert M. Patton (IJCNN, 2020)

Automated Design of Neuromorphic Networks for Scientific Applications at the Edge. - Catherine D. Schuman; J. Parker Mitchell; Maryam Parsa; James S. Plank; Samuel D. Brown; Garrett S. Rose; Robert M. Patton; Thomas E. Potok (IJCNN, 2020)

FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks. - Hui Guan 001; Laxmikant Kishor Mokadam; Xipeng Shen; Seung-Hwan Lim; Robert M. Patton (MLSys, 2020)

Caspian: A Neuromorphic Development Platform. - J. Parker Mitchell; Catherine D. Schuman; Robert M. Patton; Thomas E. Potok (NICE, 2020)

Evolutionary Optimization for Neuromorphic Systems. - Catherine D. Schuman; J. Parker Mitchell; Robert M. Patton; Thomas E. Potok; James S. Plank (NICE, 2020)

Scalable knowledge graph analytics at 136 petaflop/s. - Ramakrishnan Kannan; Piyush Sao; Hao Lu 001; Drahomira Herrmannova; Vijay Thakkar; Robert M. Patton; Richard W. Vuduc; Thomas E. Potok (SC, 2020)

Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis. - Seung-Hwan Lim; Junghoon Chae; Guojing Cong; Drahomira Herrmannova; Robert M. Patton; Ramakrishnan Kannan; Thomas E. Potok (IEEE BigData, 2021)

Diagnosing autonomous vehicle driving criteria with an adversarial evolutionary algorithm. - Mark A. Coletti; Shang Gao 008; Spencer Paulissen; Nicholas Quentin Haas; Robert M. Patton (GECCO Companion, 2021)

Computational Complexity of Neuromorphic Algorithms. - Prasanna Date; Bill Kay; Catherine D. Schuman; Robert M. Patton; Thomas E. Potok (ICONS, 2021)

Neuromorphic Computing for Autonomous Racing. - 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 (ICONS, 2021)

Quantitative Evaluation of Autonomous Driving in CARLA. - Shang Gao 008; Spencer Paulissen; Mark Coletti; Robert M. Patton (IV Workshops, 2021)

Weak Supervision for Scientific Document Relevance Tagging. - Drahomira Herrmannova; Chathika Gunaratne; Vickie Walker; Andrew A. Rooney; Robert M. Patton; Mary Wolfe; Charles Schmitt (JCDL, 2021)

An Oracle and Observations for the OpenAI Gym / ALE Freeway Environment. - James S. Plank; Catherine D. Schuman; Robert M. Patton (CoRR, 2021)

Towards establishing a research lineage via identification of significant citations. - Tirthankar Ghosal; Piyush Tiwary; Robert M. Patton; Christopher G. Stahl (Quant. Sci. Stud., 2021)

Genetic programming for understanding cognitive biases that generate polarization in social networks. - Chathika Gunaratne; Robert M. Patton (GECCO Companion, 2022)

Training reinforcement learning models via an adversarial evolutionary algorithm. - Mark Coletti; Chathika Gunaratne; Catherine D. Schuman; Robert M. Patton (ICPP Workshops, 2022)

A Framework to Enable Top-Down Co-Design of Neuromorphic Systems for Real-World Applications. - Catherine D. Schuman; James S. Plank; Robert M. Patton; Thomas E. Potok; Garrett S. Rose (NICE, 2022)

Exaflops Biomedical Knowledge Graph Analytics. - Ramakrishnan Kannan; Piyush Sao; Hao Lu 001; Jakub Kurzak; Gundolf Schenk; Yongmei Shi; Seung-Hwan Lim; Sharat Israni; Vijay Thakkar; Guojing Cong; Robert M. Patton; Sergio E. Baranzini; et al. (SC, 2022)

Neuromorphic Computing for Scientific Applications. - 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 (RSDHA@SC, 2022)

Evolutionary vs imitation learning for neuromorphic control at the edge. - 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 (Neuromorph. Comput. Eng., 2022)

SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing. - Prasanna Date; Chathika Gunaratne; Shruti R. Kulkarni; Robert M. Patton; Mark Coletti; Thomas E. Potok (ICONS, 2023)

Efficacy of using a dynamic length representation vs. a fixed-length for neuroarchitecture search. - Mark Coletti; Chathika Gunaratne; Steven R. Young; Swetha Varadarajan; Robert M. Patton; Thomas E. Potok (GECCO Companion, 2024)

A Suppression-based STDP Rule Resilient to Jitter Noise in Spike Patterns for Neuromorphic Computing. - Ashish Gautam; Takashi Kohno; Prasanna Date; Robert M. Patton; Thomas E. Potok (ICONS, 2024)

AI-Powered Knowledge Graphs for Neuromorphic and Energy-Efficient Computing. - Ashish Gautam; Robert M. Patton; Thomas E. Potok; Ramakrishnan Kannan; James B. Aimone; William Severa (ACM Great Lakes Symposium on VLSI, 2025)

NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning. - Ashish Gautam; Prasanna Date; Shruti R. Kulkarni; Robert M. Patton; Thomas E. Potok (CoRR, 2025)