T. Potok

Thomas E. Potok, Adel Said Elmaghraby, Xiaohui Cui, 2005, Sixth International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and First ACIS International Workshop on Self-Assembling Wireless Network.

Collaborative Management Environment

Nenad Ivezic, Thomas E. Potok, T. Potok, 1999 .

Machine Learning and Understanding for Intelligent Extreme Scale Scientific Computing and Discovery. DOE Workshop Report, January 7–9, 2015, Rockville, MD

Prasanna Balaprakash, Prabhat, Thomas E. Potok, 2015 .

Encoding integers and rationals on neuromorphic computers using virtual neuron

Catherine D. Schuman, Aaron R. Young, Shruti R. Kulkarni, 2022, Scientific reports.

Scalable Knowledge Graph Analytics at 136 Petaflop/s

R. Kannan, R. Vuduc, T. Potok, 2020, SC20: International Conference for High Performance Computing, Networking, Storage and Analysis.

1 Understanding the Emergence of Self-organized Insurgent Groups ( Stage Report )

Justin M. Beaver, Xiaohui Cui, T. Potok, 2008 .

The Effects of the Business Model on Object-Oriented Software Development Productivity

Mladen A. Vouk, Thomas E. Potok, T. Potok, 1997, IBM Syst. J..

Discovering event evidence amid massive, dynamic datasets

Thomas E. Potok, Robert M. Patton, T. Potok, 2007, GECCO '07.

Adaptive Sampling of Text Documents

Thomas E. Potok, Robert M. Patton, T. Potok, 2004, IASSE.

Discovery, analysis, and characteristics of event impacts

Thomas E. Potok, Robert M. Patton, Ryan A. Kerekes, 2008, 2008 11th International Conference on Information Fusion.

Neuromorphic Computing, Architectures, Models, and Applications. A Beyond-CMOS Approach to Future Computing, June 29-July 1, 2016, Oak Ridge, TN

Catherine D. Schuman, Thomas E. Potok, Robert M. Patton, 2016 .

Efficiently embedding QUBO problems on adiabatic quantum computers

Catherine D. Schuman, T. Potok, Prasanna Date, 2019, Quantum Information Processing.

A Survey of Neuromorphic Computing and Neural Networks in Hardware pdf

Catherine D. Schuman, J. Douglas Birdwell, Mark E. Dean, 2017, ArXiv.

Neuromorphic Computing is Turing-Complete pdf

Catherine D. Schuman, Prasanna Date, Catherine Schuman, 2021, ICONS.

Neuromorphic Graph Algorithms: Cycle Detection, Odd Cycle Detection, and Max Flow

Catherine D. Schuman, Prasanna Date, Catherine Schuman, 2021, ICONS.

Neuromorphic Computing for Autonomous Racing

Catherine D. Schuman, Thomas E. Potok, Prasanna Date, 2021, ICONS.

Computational Complexity of Neuromorphic Algorithms

Catherine D. Schuman, Prasanna Date, Catherine Schuman, 2021, ICONS.

Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers

Catherine D. Schuman, Thomas E. Potok, Prasanna Date, 2021, 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).

Caspian: A Neuromorphic Development Platform

Catherine D. Schuman, Thomas E. Potok, Robert M. Patton, 2020, NICE.

Bayesian Multi-objective Hyperparameter Optimization for Accurate, Fast, and Efficient Neural Network Accelerator Design

Catherine D. Schuman, Kaushik Roy, Thomas E. Potok, 2020, Frontiers in Neuroscience.

Productivity analysis of object‐oriented software developed in a commercial environment

Mladen A. Vouk, Thomas E. Potok, Andy Rindos, 1999 .

Productivity Analysis of Object-Oriented Software Development in a Commercial Environment

Mladen A. Vouk, Thomas E. Potok, Andrew Rindos, 1999, Softw. Pract. Exp..

Semantic-based information retrieval of biomedical data

Ali R. Hurson, Yu Jiao, Thomas E. Potok, 2006, SAC.

A bridge for accelerating materials by design

Thomas E. Potok, Bobby G. Sumpter, Sergei V. Kalinin, 2015 .

Classification of Distributed Data Using Topic Modeling and Maximum Variation Sampling

Thomas E. Potok, Robert M. Patton, Justin M. Beaver, 2011, 2011 44th Hawaii International Conference on System Sciences.

Bayesian-based Hyperparameter Optimization for Spiking Neuromorphic Systems

Catherine D. Schuman, Kaushik Roy, Thomas E. Potok, 2019, 2019 IEEE International Conference on Big Data (Big Data).

Adiabatic quantum linear regression pdf

Prasanna Date, Thomas Potok, T. Potok, 2020, Scientific Reports.

A flocking based algorithm for document clustering analysis

Thomas E. Potok, Xiaohui Cui, Jinzhu Gao, 2006, J. Syst. Archit..

Multimedia correlation analysis in unstructured peer-to-peer networks

Bo Yang, Ali R. Hurson, Yu Jiao, 2006, 2006 International Symposium on a World of Wireless, Mobile and Multimedia Networks(WoWMoM'06).

Efficiently embedding QUBO problems on adiabatic quantum computers

Catherine D. Schuman, Thomas E. Potok, Prasanna Date, 2019, Quantum Information Processing.

Adiabatic Quantum Computation Applied to Deep Learning Networks

Catherine D. Schuman, Steven R. Young, Garrett S. Rose, 2018, Entropy.

A Classical-Quantum Hybrid Approach for Unsupervised Probabilistic Machine Learning

Catherine D. Schuman, Thomas E. Potok, Prasanna Date, 2019, Lecture Notes in Networks and Systems.

Analysis and Classification ofMammography Reports using Maximum Variation Sampling

Thomas E. Potok, Robert M. Patton, Barbara G. Beckerman, 2010, Genetic and Evolutionary Computation: Medical Applications.

Genetic algorithm for analysis of abdominal aortic aneurysms in radiology reports

Thomas E. Potok, Robert M. Patton, Barbara G. Beckerman, 2010, GECCO '10.

A genetic algorithm for learning significant phrase patterns in radiology reports

Thomas E. Potok, Robert M. Patton, Barbara G. Beckerman, 2009, GECCO '09.

Learning cue phrase patterns from radiology reports using a genetic algorithm

Thomas E. Potok, Robert M. Patton, Barbara G. Beckerman, 2009, 2009 First Annual ORNL Biomedical Science & Engineering Conference.

Analysis of mammography reports using maximum variation sampling

Thomas E. Potok, Robert M. Patton, Barbara G. Beckerman, 2008, GECCO '08.

Document clustering using particle swarm optimization

Thomas E. Potok, Xiaohui Cui, Paul J. Palathingal, 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

Vector space model for the generalized parts grouping problem

Thomas E. Potok, Michael R. Leuze, Nagiza Faridovna Samatova, 2001 .

A VECTOR PERTURBATION APPROACH TO THE GENERALIZED AIRCRAFT SPARE PARTS GROUPING PROBLEM

Nagiza F. Samatova, Thomas E. Potok, Michael R. Leuze, 2000 .

Evolving Energy Efficient Convolutional Neural Networks

Catherine D. Schuman, Steven R. Young, Thomas E. Potok, 2019, 2019 IEEE International Conference on Big Data (Big Data).

Dimensionality reduction particle swarm algorithm for high dimensional clustering

Thomas E. Potok, Xiaohui Cui, Justin M. Beaver, 2008, 2008 IEEE Swarm Intelligence Symposium.

Clustering using Particle Swarm Optimization ( Extended

Thomas E. Potok, Xiaohui Cui, Xiaohui Cui, 2005 .

Clustering Analysis Based on Hybrid PSO + K-means Algorithm

Xiaohui Cui, T. Potok, 2005 .

A Small, Low Cost Event-Driven Architecture for Spiking Neural Networks on FPGAs

Catherine D. Schuman, Thomas E. Potok, J. Parker Mitchell, 2020, ICONS.

SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing

Shruti R. Kulkarni, Robert M. Patton, T. Potok, 2023, ICONS.

Evolutionary Optimization for Neuromorphic Systems

Catherine D. Schuman, Thomas E. Potok, Robert M. Patton, 2020, NICE.

The Swarm Model in Open Source Software Developer Communities

Thomas E. Potok, Xiaohui Cui, Everett Stiles, 2010, 2010 IEEE Second International Conference on Social Computing.

A Stigmergy Approach for Open Source Software Developer Community Simulation

Thomas E. Potok, Xiaohui Cui, Justin M. Beaver, 2009, 2009 International Conference on Computational Science and Engineering.

A Stigmergy Collaboration Approach in the Open Source Software Developer Community

Thomas E. Potok, Laura L. Pullum, Xiaohui Cui, 2009 .

The GPU Enhanced Parallel Computing for Large Scale Data Clustering

Thomas E. Potok, Xiaohui Cui, Jesse St. Charles, 2011, 2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery.

An ontology-based HTML to XML conversion using intelligent agents

Nagiza F. Samatova, Thomas E. Potok, Mark T. Elmore, 2002, Proceedings of the 35th Annual Hawaii International Conference on System Sciences.

A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers

Catherine D. Schuman, Steven R. Young, Garrett S. Rose, 2016, 2016 2nd Workshop on Machine Learning in HPC Environments (MLHPC).

167-PFlops Deep Learning for Electron Microscopy: From Learning Physics to Atomic Manipulation

Catherine D. Schuman, Steven R. Young, Thomas P. Karnowski, 2018, SC18: International Conference for High Performance Computing, Networking, Storage and Analysis.

Modeling with Stochastic Message Sequence Charts

Frederick T. Sheldon, T. Potok, Zhihe Zhou, 2003 .

Large-scale multi-dimensional document clustering on GPU clusters

Frank Mueller, Thomas E. Potok, Xiaohui Cui, 2010, 2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS).

Swarm Intelligence in Text Document Clustering

Thomas E. Potok, Xiaohui Cui, Xiaohui Cui, 2008 .

Audience Based View of Publication Impact

Thomas E. Potok, Robert M. Patton, Jack C. Wells, 2017, WOSP@JCDL.

Particle Swarm Social Adaptive Model for Multi-Agent Based Insurgency Warfare Simulation

Thomas E. Potok, Xiaohui Cui, Xiaohui Cui, 2009 .

Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment

Catherine D. Schuman, Steven R. Young, Derek C. Rose, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Visualization System for Evolutionary Neural Networks for Deep Learning

Catherine D. Schuman, Steven R. Young, Thomas E. Potok, 2019, 2019 IEEE International Conference on Big Data (Big Data).

ASCR Cybersecurity for Scientific Computing Integrity - Research Pathways and Ideas Workshop

Thomas E. Potok, Sean Peisert, Todd Jones, 2015 .

Visual Mining Intrusion Behaviors by Using Swarm Technology

Li Yang, Thomas E. Potok, Xiaohui Cui, 2011, 2011 44th Hawaii International Conference on System Sciences.

TF-ICF: A New Term Weighting Scheme for Clustering Dynamic Data Streams

Ali R. Hurson, Thomas E. Potok, Mark T. Elmore, 2006, 2006 5th International Conference on Machine Learning and Applications (ICMLA'06).

Multi-year Content Analysis of User Facility Related Publications

Thomas E. Potok, Robert M. Patton, Jack C. Wells, 2013, D Lib Mag..

A Distributed Agent Implementation of Multiple Species Flocking Model for Document Partitioning Clustering

Thomas E. Potok, Xiaohui Cui, Xiaohui Cui, 2006, CIA.

Distributed Adaptive Particle Swarm Optimizer in Dynamic Environment

Thomas E. Potok, Xiaohui Cui, Xiaohui Cui, 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

Particle Swarm Social Model for Group Social Learning in Adaptive Environment

Thomas E. Potok, Laura L. Pullum, Robert M. Patton, 2008 .

A Simple Distributed Particle Swarm Optimization for Dynamic and Noisy Environments

Thomas E. Potok, Xiaohui Cui, Jesse St. Charles, 2008, NICSO.

Particle Swarm Based Collective Searching Model for Adaptive Environment

Thomas E. Potok, Robert M. Patton, Xiaohui Cui, 2007, NICSO.

Caspian

Catherine D. Schuman, T. Potok, J. P. Mitchell, 2020, Proceedings of the Neuro-inspired Computational Elements Workshop.

Parallel latent semantic analysis using a graphics processing unit

Thomas E. Potok, Xiaohui Cui, Joseph M. Cavanagh, 2009, GECCO '09.

Semi-Supervised Graph Structure Learning on Neuromorphic Computers

Catherine D. Schuman, Shruti R. Kulkarni, T. Potok, 2022, ICONS.

Neuromorphic Computing for Scientific Applications

Steven R. Young, Shruti R. Kulkarni, T. Potok, 2022, 2022 IEEE/ACM Redefining Scalability for Diversely Heterogeneous Architectures Workshop (RSDHA).

Evolutionary vs imitation learning for neuromorphic control at the edge

Catherine D. Schuman, Christopher G. Stahl, Shruti R. Kulkarni, 2021, Neuromorph. Comput. Eng..

Neuromorphic computing for temporal scientific data classification

Catherine D. Schuman, Steven R. Young, Garrett S. Rose, 2017, NCS.

A Framework to Enable Top-Down Co-Design of Neuromorphic Systems for Real-World Applications

Catherine D. Schuman, J. Plank, T. Potok, 2022, Neuro Inspired Computational Elements Workshop.

Exascale Deep Learning to Accelerate Cancer Research

Catherine D. Schuman, Steven R. Young, Derek C. Rose, 2019, 2019 IEEE International Conference on Big Data (Big Data).

Deep Learning for Vertex Reconstruction of Neutrino-nucleus Interaction Events with Combined Energy and Time Data

Catherine D. Schuman, Steven R. Young, Thomas E. Potok, 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Evolving Deep Networks Using HPC

Steven R. Young, Thomas P. Karnowski, Derek C. Rose, 2017, MLHPC@SC.

Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis

Thomas E. Potok, Ramakrishnan Kannan, Junghoon Chae, 2021, 2021 IEEE International Conference on Big Data (Big Data).

Fine-Grained Exploitation of Mixed Precision for Faster CNN Training

Catherine D. Schuman, Steven R. Young, Thomas E. Potok, 2019, 2019 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC).

A Distributed Flocking Approach for Information Stream Clustering Analysis

Thomas E. Potok, Xiaohui Cui, Xiaohui Cui, 2006, Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD'06).

Discovering Potential Precursors of Mammography Abnormalities Based on Textual Features, Frequencies, and Sequences

Thomas E. Potok, Robert M. Patton, T. Potok, 2010, ICAISC.

Autonomic Approach to Survivable Cyber-Secure Infrastructures

Thomas E. Potok, Frederick T. Sheldon, Paul W. Oman, 2004 .

Multi-Agent System Case Studies in Command and Control , Information Fusion and Data Management

Frederick T. Sheldon, Frederick Sheldon, Thomas Potok, 2004 .

Multi-Agent System Case Studies in Command and Control, Information Fusion and Datat Managment

Krishna M. Kavi, Thomas E. Potok, Frederick T. Sheldon, 2004, Informatica.

Characterizing large text corpora using a maximum variation sampling genetic algorithm

Thomas E. Potok, Robert M. Patton, T. Potok, 2006, GECCO.

Multiagent Framework for Transitional Operations

Nenad Ivezic, Thomas E. Potok, Line C. Pouchard, 1999 .