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Journal Articles
- 2023
[j6]Russell B. Davidson
, Mark Coletti, Mu Gao, Bryan Piatkowski, Avinash Sreedasyam, Farhan Quadir, David J. Weston, Jeremy Schmutz, Jianlin Cheng, Jeffrey Skolnick, Jerry M. Parks, Ada Sedova:
Predicted structural proteome of Sphagnum divinum and proteome-scale annotation. Bioinform. 39(8) (2023)- [j5]Eric O. Scott, Mark Coletti, Catherine D. Schuman, Bill Kay, Shruti R. Kulkarni, Maryam Parsa, Chathika Gunaratne, Kenneth A. De Jong:
Avoiding excess computation in asynchronous evolutionary algorithms. Expert Syst. J. Knowl. Eng. 40(5) (2023) - 2022
- [j4]Addi Malviya-Thakur, David E. Bernholdt, William F. Godoy, Gregory R. Watson, Mathieu Doucet, Mark A. Coletti, David M. Rogers, Marshall T. McDonnell, Jay Jay Billings, Barney Maccabe:
Research Software Engineering at Oak Ridge National Laboratory. Comput. Sci. Eng. 24(5): 14-23 (2022) - 2020
- [j3]Mark Coletti, Alex Fafard, David Page:
Troubleshooting deep-learner training data problems using an evolutionary algorithm on Summit. IBM J. Res. Dev. 64(3/4): 1-12 (2020) - [j2]Alexander J. Fafard, Jan van Aardt, Mark Coletti, David L. Page:
Global Partitioning Elevation Normalization Applied to Building Footprint Prediction. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13: 3493-3502 (2020) - 2019
- [j1]Kuldeep R. Kurte, Jibonananda Sanyal, Anne Berres, Dalton D. Lunga, Mark Coletti, Hsiuhan Lexie Yang, Daniel Graves, Benjamin Liebersohn, Amy N. Rose:
Performance analysis and optimization for scalable deployment of deep learning models for country-scale settlement mapping on Titan supercomputer. Concurr. Comput. Pract. Exp. 31(20) (2019)
Conference and Workshop Papers
- 2024
- [c22]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: 1888-1894 - [c21]Tyler J. Skluzacek, Renan Souza, Mark Coletti, Frédéric Suter, Rafael Ferreira da Silva:
Towards Cross-Facility Workflows Orchestration through Distributed Automation. PEARC 2024: 72:1-72:4 - 2023
- [c20]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: 40:1-40:4 - [c19]Mark Coletti, Ada Sedova, Rajni Chahal, Luke Gibson, Santanu Roy, Vyacheslav Bryantsev:
Multiobjective Hyperparameter Optimization for Deep Learning Interatomic Potential Training Using NSGA-II. ICPP Workshops 2023: 172-179 - 2022
- [c18]Mark Coletti, Chathika Gunaratne, Catherine D. Schuman, Robert M. Patton:
Training reinforcement learning models via an adversarial evolutionary algorithm. ICPP Workshops 2022: 23:1-23:6 - [c17]Mu Gao, Mark Coletti, Russell B. Davidson, Ryan Prout, Subil Abraham, Benjamín Hernández, Ada Sedova:
Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer. IPDPS Workshops 2022: 206-215 - [c16]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: 22-28 - 2021
- [c15]Maryam Parsa, Shruti R. Kulkarni, Mark Coletti, Jeffrey K. Bassett, J. Parker Mitchell, Catherine D. Schuman:
Multi-Objective Hyperparameter Optimization for Spiking Neural Network Neuroevolution. CEC 2021: 1225-1232 - [c14]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: 301-302 - [c13]Shang Gao, Spencer Paulissen, Mark Coletti, Robert M. Patton:
Quantitative Evaluation of Autonomous Driving in CARLA. IV Workshops 2021: 257-263 - [c12]Pravallika Devineni, Panchapakesan Ganesh, Nikhil Sivadas, Abhijeet Dhakane, Ketan Maheshwari, Drahomira Herrmannova, Ramakrishnan Kannan, Seung-Hwan Lim, Thomas E. Potok, Jordan B. Chipka, Priyantha Mudalige, Mark Coletti, Sajal Dash, Arnab Kumar Paul, Sarp Oral, Feiyi Wang, Bill Kay, Melissa R. Allen-Dumas, Christa Brelsford, Joshua R. New, Andy Berres, Kuldeep R. Kurte, Jibonananda Sanyal, Levi Sweet, Chathika Gunaratne, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin, Olivera Kotevska, Jean C. Bilheux, Hassina Z. Bilheux, Garrett E. Granroth, Thomas Proffen, Rick Riedel, Peter F. Peterson, Shruti R. Kulkarni, Kyle P. Kelley, Stephen Jesse, Maryam Parsa:
Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. SMC 2021: 361-382 - [c11]Eric O. Scott, Mark Coletti, Catherine D. Schuman, Bill Kay, Shruti R. Kulkarni, Maryam Parsa, Kenneth A. De Jong:
Avoiding Excess Computation in Asynchronous Evolutionary Algorithms. UKCI 2021: 71-82 - 2020
- [c10]Mark Coletti, Eric O. Scott, Jeffrey K. Bassett:
Library for evolutionary algorithms in Python (LEAP). GECCO Companion 2020: 1571-1579 - 2019
- [c9]Mark Coletti, Dalton D. Lunga, Jeffrey K. Bassett, Amy N. Rose:
Evolving Larger Convolutional Layer Kernel Sizes for a Settlement Detection Deep-Learner on Summit. DLS@SC 2019: 36-44 - 2012
- [c8]Mark Coletti:
The effects of training set size and keeping rules on the emergent selection pressure of learnable evolution model. GECCO (Companion) 2012: 1505-1506 - [c7]Mark Coletti, Guido Cervone:
Analysis of Emergent Selection Pressure in Evolutionary Algorithm and Machine Learner Offspring Filtering Hybrids. SEMCCO 2012: 721-728 - [c6]William G. Kennedy, Chenna Reddy Cotla, Tim Gulden, Mark Coletti, Claudio Cioffi-Revilla:
Towards Validating a Model of Households and Societies in East Africa. WCSS 2012: 315-328 - 2010
- [c5]Michael Q. Kalish, Alexei V. Samsonovich, Mark Coletti, Kenneth A. De Jong:
Assessing the Role of Metacognition in GMU BICA. BICA 2010: 72-77 - 2009
- [c4]Jeffrey K. Bassett, Mark Coletti, Kenneth A. De Jong:
The relationship between evolvability and bloat. GECCO 2009: 1899-1900 - [c3]Mark Coletti:
Learnable evolution model performance impaired by binary tournament survival selection. GECCO (Companion) 2009: 2717-2720 - 2002
- [c2]Mark Coletti:
A preliminary study of learnable evolution methodology implemented with C4.5. IEEE Congress on Evolutionary Computation 2002: 588-593 - 1999
- [c1]Mark Coletti, Thomas D. Lash, Ryszard S. Michalski, Craig Mandsager, Rida E. Moustafa:
Comparing Performance of the Learnable Evolution Model and Genetic Algorithms. GECCO 1999: 779
Informal and Other Publications
- 2024
- [i2]Sanjif Shanmugavelu, Mathieu Taillefumier, Christopher Culver, Oscar R. Hernandez, Mark Coletti, Ada Sedova:
Impacts of floating-point non-associativity on reproducibility for HPC and deep learning applications. CoRR abs/2408.05148 (2024) - 2023
- [i1]Prasanna Date, Chathika Gunaratne, Shruti R. Kulkarni, Robert M. Patton, Mark Coletti, Thomas E. Potok:
SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing. CoRR abs/2305.02510 (2023)
Coauthor Index
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