J. Luc Peterson

21 papers C 1Journal 18Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Constrained Multi-Fidelity Bayesian Optimization Method. CoRR Jingyi Wang, Naiyuan Chiang, Tucker Hartland, J. Luc Peterson, Jerome Solberg, Cosmin G. Petra
2025	J	`jnl`	A Terminology for Scientific Workflow Systems. CoRR Frédéric Suter, Tainã Coleman, Ilkay Altintas, Rosa M. Badia, Bartosz Balis, Kyle Chard, Iacopo Colonnelli, Ewa Deelman, Paolo Di Tommaso, Thomas Fahringer, Carole A. Goble, Shantenu Jha, Daniel S. Katz, Johannes Köster, Ulf Leser, Kshitij Mehta, Hilary Oliver, J. Luc Peterson, Giovanni Pizzi, Loïc Pottier, Raül Sirvent, Eric Suchyta, Douglas Thain, Sean R. Wilkinson, Justin M. Wozniak, Rafael Ferreira da Silva
2023	J	`jnl`	A multifidelity Bayesian optimization method for inertial confinement fusion design. CoRR Jingyi Wang, Nai Yuan Chiang, Andrew Gillette, J. Luc Peterson
2022	J	`jnl`	Enabling machine learning-ready HPC ensembles with Merlin. Future Gener. Comput. Syst. J. Luc Peterson, Benjamin Bay, Joe Koning, Peter B. Robinson, Jessica Semler, Jeremy White, Rushil Anirudh, Kevin Athey, Peer-Timo Bremer, Francesco Di Natale, David Fox, Jim A. Gaffney, Sam Ade Jacobs, Bhavya Kailkhura, Bogdan Kustowski, Steve H. Langer, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom
2021	—	`conf`	A Community Roadmap for Scientific Workflows Research and Development. WORKS Rafael Ferreira da Silva, Henri Casanova, Kyle Chard, Ilkay Altintas, Rosa M. Badia, Bartosz Balis, Tainã Coleman, Frederik Coppens, Frank Di Natale, Bjoern Enders, Thomas Fahringer, Rosa Filgueira, Grigori Fursin, Daniel Garijo, Carole A. Goble, Dorran Howell, Shantenu Jha, Daniel S. Katz, Daniel E. Laney, Ulf Leser, Maciej Malawski, Kshitij Mehta, Loïc Pottier, Jonathan Ozik, J. Luc Peterson, Lavanya Ramakrishnan, Stian Soiland-Reyes, Douglas Thain, Matthew Wolf
2021	J	`jnl`	A Community Roadmap for Scientific Workflows Research and Development. CoRR Rafael Ferreira da Silva, Henri Casanova, Kyle Chard, Ilkay Altintas, Rosa M. Badia, Bartosz Balis, Tainã Coleman, Frederik Coppens, Frank Di Natale, Bjoern Enders, Thomas Fahringer, Rosa Filgueira, Grigori Fursin, Daniel Garijo, Carole A. Goble, Dorran Howell, Shantenu Jha, Daniel S. Katz, Daniel E. Laney, Ulf Leser, Maciej Malawski, Kshitij Mehta, Loïc Pottier, Jonathan Ozik, J. Luc Peterson, Lavanya Ramakrishnan, Stian Soiland-Reyes, Douglas Thain, Matthew Wolf
2021	J	`jnl`	Cognitive simulation models for inertial confinement fusion: Combining simulation and experimental data. CoRR Kelli D. Humbird, J. Luc Peterson, J. Salmonson, Brian K. Spears
2021	J	`jnl`	The data-driven future of high-energy-density physics. Nat. Peter W. Hatfield, Jim A. Gaffney, Gemma J. Anderson, Suzanne Ali, Luca Antonelli, Suzan Basegmez du Pree, Jonathan Citrin, Marta Fajardo, Patrick F. Knapp, Brendan Kettle, Bogdan Kustowski, Michael J. MacDonald, Derek Mariscal, Madison E. Martin, Taisuke Nagayama, Charlotte A. J. Palmer, J. Luc Peterson, Steven J. Rose, J. J. Ruby, Carl Shneider, Matt J. V. Streeter, Will Trickey, Ben Williams
2021	J	`jnl`	Workflows Community Summit: Bringing the Scientific Workflows Community Together. CoRR Rafael Ferreira da Silva, Henri Casanova, Kyle Chard, Dan Laney, Dong H. Ahn, Shantenu Jha, Carole A. Goble, Lavanya Ramakrishnan, J. Luc Peterson, Bjoern Enders, Douglas Thain, Ilkay Altintas, Yadu N. Babuji, Rosa M. Badia, Vivien Bonazzi, Tainã Coleman, Michael R. Crusoe, Ewa Deelman, Frank Di Natale, Paolo Di Tommaso, Thomas Fahringer, Rosa Filgueira, Grigori Fursin, Alex Ganose, Björn A. Grüning, Daniel S. Katz, Olga A. Kuchar, Ana Kupresanin, Bertram Ludäscher, Ketan Maheshwari, Marta Mattoso, Kshitij Mehta, Todd S. Munson, Jonathan Ozik, Tom Peterka, Loic Pottier, Tim Randles, Stian Soiland-Reyes, Benjamín Tovar, Matteo Turilli, Thomas D. Uram, Karan Vahi, Michael Wilde, Matthew Wolf, Justin M. Wozniak
2020	J	`jnl`	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. IEEE Trans. Vis. Comput. Graph. Shusen Liu, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom
2019	J	`jnl`	Deep Neural Network Initialization With Decision Trees. IEEE Trans. Neural Networks Learn. Syst. Kelli D. Humbird, J. Luc Peterson, Ryan G. McClarren
2019	J	`jnl`	Merlin: Enabling Machine Learning-Ready HPC Ensembles. CoRR J. Luc Peterson, Rushil Anirudh, Kevin Athey, Benjamin Bay, Peer-Timo Bremer, Vic Castillo, Francesco Di Natale, David Fox, Jim A. Gaffney, David Hysom, Sam Ade Jacobs, Bhavya Kailkhura, Joe Koning, Bogdan Kustowski, Steven H. Langer, Peter B. Robinson, Jessica Semler, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom
2019	C	`conf`	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CLUSTER Sam Ade Jacobs, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer
2019	J	`jnl`	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CoRR Sam Ade Jacobs, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears
2019	J	`jnl`	Parameter inference with deep jointly informed neural networks. Stat. Anal. Data Min. Kelli D. Humbird, J. Luc Peterson, Ryan G. McClarren
2019	J	`jnl`	Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. CoRR Shusen Liu, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer
2018	J	`jnl`	Predicting the time-evolution of multi-physics systems with sequence-to-sequence models. CoRR Kelli D. Humbird, J. Luc Peterson, Ryan G. McClarren
2018	J	`jnl`	Transfer learning to model inertial confinement fusion experiments. CoRR Kelli D. Humbird, J. Luc Peterson, Ryan G. McClarren
2017	J	`jnl`	Deep Jointly-Informed Neural Networks. CoRR Kelli D. Humbird, J. Luc Peterson, Ryan G. McClarren
2016	—	`conf`	A HYDRA UQ Workflow for NIF Ignition Experiments. ISAV@SC Steven H. Langer, Brian K. Spears, J. Luc Peterson, John Everett Field, Ryan Nora, Scott Brandon
2013	J	`jnl`	Positivity Preservation and Advection Algorithms with Applications to Edge Plasma Turbulence. SIAM J. Sci. Comput. J. Luc Peterson, Gregory W. Hammett