Search Results - "Coletti, Mark"

Assessing Impacts of Atmospheric Conditions on Efficiency and Siting of Large-Scale Direct Air Capture Facilities by Cai, Xuqing, Coletti, Mark A., Sholl, David S., Allen-Dumas, Melissa R.

“…The cost and efficiency of direct air capture (DAC) of carbon dioxide (CO2) will be decisive in determining whether this technology can play a large role in…”
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Research Software Engineering at Oak Ridge National Laboratory by Malviya-Thakur, Addi, Bernholdt, David E., Godoy, William F., Watson, Gregory R., Doucet, Mathieu, Coletti, Mark A., Rogers, David M., McDonnell, Marshall, Billings, Jay Jay, Maccabe, Barney

“…Research software engineers (RSE) play a vital role in scientific discoveries worldwide. They lead the core development of the applications, libraries, and…”
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Performance analysis and optimization for scalable deployment of deep learning models for country‐scale settlement mapping on Titan supercomputer by Kurte, Kuldeep, Sanyal, Jibonananda, Berres, Anne, Lunga, Dalton, Coletti, Mark, Yang, Hsiuhan Lexie, Graves, Daniel, Liebersohn, Benjamin, Rose, Amy

“…Summary This paper presents a scalable object detection workflow for detecting objects, such as settlements, from remotely sensed (RS) imagery. We have…”
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Global Partitioning Elevation Normalization Applied to Building Footprint Prediction by Fafard, Alexander, van Aardt, Jan, Coletti, Mark, Page, David L.

“…Understanding and exploiting topographical data via standard machine learning techniques is challenging, mainly due to the large dynamic range of values…”
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A dataset of recorded electricity outages by United States county 2014–2022 by Brelsford, Christa, Tennille, Sarah, Myers, Aaron, Chinthavali, Supriya, Tansakul, Varisara, Denman, Matthew, Coletti, Mark, Grant, Joshua, Lee, Sangkeun, Allen, Karl, Johnson, Evelyn, Huihui, Jonathan, Hamaker, Alec, Newby, Scott, Medlen, Kyle, Maguire, Dakotah, Dunivan Stahl, Chelsey, Moehl, Jessica, Redmon, Daniel, Sanyal, Jibonananda, Bhaduri, Budhendra

“…In this Data Descriptor, we present county-level electricity outage estimates at 15-minute intervals from 2014 to 2022. By 2022 92% of customers in the 50 US…”
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Predicted structural proteome of Sphagnum divinum and proteome-scale annotation by Davidson, Russell B, Coletti, Mark, Gao, Mu, Piatkowski, Bryan, Sreedasyam, Avinash, Quadir, Farhan, Weston, David J, Schmutz, Jeremy, Cheng, Jianlin, Skolnick, Jeffrey, Parks, Jerry M, Sedova, Ada

“…Abstract Motivation Sphagnum-dominated peatlands store a substantial amount of terrestrial carbon. The genus is undersampled and under-studied. No experimental…”
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Global Partitioning Elevation Normalization Applied to Building Footprint Prediction by Fafard, Alexander, van Aardt, Jan, Coletti, Mark, Page, David L.

“…Understanding and exploiting topographical data via standard machine learning techniques is challenging, mainly due to the large dynamic range of values…”
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Validating Safecast data by comparisons to a U. S. Department of Energy Fukushima Prefecture aerial survey by Coletti, Mark, Hultquist, Carolynne, Kennedy, William G., Cervone, Guido

“…Safecast is a volunteered geographic information (VGI) project where the lay public uses hand-held sensors to collect radiation measurements that are then made…”
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Avoiding excess computation in asynchronous evolutionary algorithms by Scott, Eric O., Coletti, Mark, Schuman, Catherine D., Kay, Bill, Kulkarni, Shruti R., Parsa, Maryam, Gunaratne, Chathika, De Jong, Kenneth A.

“…Asynchronous evolutionary algorithms are becoming increasingly popular as a means of making full use of many processors while solving computationally expensive…”
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Avoiding excess computation in asynchronous evolutionary algorithms by Scott, Eric O., Coletti, Mark, Schuman, Catherine D., Kay, Bill, Kulkarni, Shruti R., Parsa, Maryam, Gunaratne, Chathika, De Jong, Kenneth A.

“…Asynchronous evolutionary algorithms are becoming increasingly popular as a means of making full use of many processors while solving computationally expensive…”
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Performance analysis and optimization for scalable deployment of deep learning models for country-scale settlement mapping on Titan supercomputer by Kurte, Kuldeep, Sanyal, Jibonananda, Berres, Anne, Lunga, Dalton, Coletti, Mark, Yang, Hsiuhan Lexie, Graves, Daniel, Liebersohn, Benjamin, Rose, Amy

“…Here, we present a scalable object detection workflow for detecting objects, such as settlements, from remotely sensed (RS) imagery. We have successfully…”
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An analysis of a model-based evolutionary algorithm: Learnable Evolution Model by Coletti, Mark

“…An evolutionary algorithm (EA) is a biologically inspired metaheuristic that uses mutation, crossover, reproduction, and selection operators to evolve…”
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Impacts of floating-point non-associativity on reproducibility for HPC and deep learning applications by Shanmugavelu, Sanjif, Taillefumier, Mathieu, Culver, Christopher, Hernandez, Oscar, Coletti, Mark, Sedova, Ada

“…Run to run variability in parallel programs caused by floating-point non-associativity has been known to significantly affect reproducibility in iterative…”
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Workflow Provenance in the Computing Continuum for Responsible, Trustworthy, and Energy-Efficient AI by Souza, Renan, Caino-Lores, Silvina, Coletti, Mark, Skluzacek, Tyler J., Costan, Alexandru, Suter, Frederic, Mattoso, Marta, Da Silva, Rafael Ferreira

“…As Artificial Intelligence (AI) becomes more pervasive in our society, it is crucial to develop, deploy, and assess Responsible and Trustworthy AI (RTAI)…”
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Quantitative Evaluation of Autonomous Driving in CARLA by Gao, Shang, Paulissen, Spencer, Coletti, Mark, Patton, Robert

“…There have been many recent advancements in imitation and reinforcement learning for autonomous driving, but existing metrics generally lack the means to…”
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SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing by Date, Prasanna, Gunaratne, Chathika, Kulkarni, Shruti, Patton, Robert, Coletti, Mark, Potok, Thomas

“…In many neuromorphic workflows, simulators play a vital role for important tasks such as training spiking neural networks (SNNs), running neuroscience…”
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Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer by Gao, Mu, Coletti, Mark, Davidson, Russell B., Prout, Ryan, Abraham, Subil, Hernandez, Benjamin, Sedova, Ada

“…Deep learning has contributed to major advances in the prediction of protein structure from sequence, a fundamental problem in structural bioinformatics. With…”
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Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer by Gao, Mu, Coletti, Mark, Davidson, Russell B, Prout, Ryan, Abraham, Subil, Hernandez, Benjamin, Sedova, Ada

“…Deep learning has contributed to major advances in the prediction of protein structure from sequence, a fundamental problem in structural bioinformatics. With…”
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Ramifications of Evolving Misbehaving Convolutional Neural Network Kernel and Batch Sizes by Coletti, Mark, Lunga, Dalton, Berres, Anne, Sanyal, Jibonananda, Rose, Amy

“…Deep-learners have many hyper-parameters including learning rate, batch size, kernel size - all playing a significant role toward estimating high quality…”
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Multi-Objective Hyperparameter Optimization for Spiking Neural Network Neuroevolution by Parsa, Maryam, Kulkarni, Shruti R., Coletti, Mark, Bassett, Jeffrey, Mitchell, J. Parker, Schuman, Catherine D.

“…Neuroevolution has had significant success over recent years, but there has been relatively little work applying neuroevolution approaches to spiking neural…”
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