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Data-driven prediction of scaling and ignition of inertial confinement fusion experiments von Gaffney, Jim A., Humbird, Kelli, Kritcher, Andrea, Kruse, Michael, Kur, Eugene, Kustowski, Bogdan, Nora, Ryan, Spears, Brian

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Making inertial confinement fusion models more predictive von Gaffney, Jim A., Brandon, Scott T., Humbird, Kelli D., Kruse, Michael K. G., Nora, Ryan C., Peterson, J. Luc, Spears, Brian K.

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Deep learning: A guide for practitioners in the physical sciences von Spears, Brian K., Brase, James, Bremer, Peer-Timo, Chen, Barry, Field, John, Gaffney, Jim, Kruse, Michael, Langer, Steve, Lewis, Katie, Nora, Ryan, Peterson, Jayson Luc, Jayaraman Thiagarajan, Jayaraman, Van Essen, Brian, Humbird, Kelli

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Transfer learning as a method to reproduce high-fidelity non-local thermodynamic equilibrium opacities in simulations von Vander Wal, Michael D., McClarren, Ryan G., Humbird, Kelli D.

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Transfer Learning of High-Fidelity Opacity Spectra in Autoencoders and Surrogate Models von Wal, Michael D. Vander, McClarren, Ryan G., Humbird, Kelli D.

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Investigating boosted decision trees as a guide for inertial confinement fusion design von Maris, Andrew D., Khan, Shahab F., Pokornik, Michael M., Peterson, J. Luc, Humbird, Kelli D., Haan, Steven W.

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Toward digital design at the exascale: An overview of project ICECap von Peterson, J. Luc, Bender, Tim, Blake, Robert, Chiang, Nai-Yuan, Fernández-Godino, M. Giselle, Garcia, Bryan, Gillette, Andrew, Gunnarson, Brian, Hansen, Cooper, Hill, Judy, Humbird, Kelli, Kustowski, Bogdan, Kim, Irene, Koning, Joe, Kur, Eugene, Langer, Steve, Lee, Ryan, Lewis, Katie, Maguire, Alister, Milovich, Jose, Mubarka, Yamen, Olson, Renee, Salmonson, Jay, Schroeder, Chris, Spears, Brian, Thiagarajan, Jayaraman, Tran, Ryan, Wang, Jingyi, Weber, Chris

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Neural network surrogate models for absorptivity and emissivity spectra of multiple elements von Vander Wal, Michael D., McClarren, Ryan G., Humbird, Kelli D.

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Investigating boosted decision trees as a guide for inertial confinement fusion design von Maris, Andrew D., Khan, Shahab F., Pokornik, Michael M., Peterson, J. Luc, Humbird, Kelli D., Haan, Steven W.

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Iterative sampling of expensive simulations for faster deep surrogate training von Gaffney, Jim A., Humbird, Kelli, Kruse, Michael, Kur, Eugene, Kustowski, Bogdan, Nora, Ryan, Spears, Brian

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Adjoint-based sensitivity analysis for high-energy density radiative transfer using flux-limited diffusion von Humbird, Kelli D., McClarren, Ryan G.

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Making inertial confinement fusion models more predictive von Gaffney, Jim A., Brandon, Scott T., Humbird, Kelli D., Kruse, Michael K. G., Nora, Ryan C., Peterson, J. Luc, Spears, Brian K.

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Adjoint-based sensitivity analysis for high-energy density radiative transfer using flux-limited diffusion von Humbird, Kelli D., McClarren, Ryan G.

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2022 Review of Data-Driven Plasma Science von Anirudh, Rushil, Archibald, Rick, Asif, M. Salman, Becker, Markus M, Benkadda, Sadruddin, Bremer, Peer-Timo, Bude, Rick H.S, Chang, C.S, Chen, Lei, Churchill, R.M, Citrin, Jonathan, Gaffney, Jim A, Gainaru, Ana, Gekelman, Walter, Gibbs, Tom, Hamaguchi, Satoshi, Hill, Christian, Humbird, Kelli, Jalas, Soeren, Kawaguchi, Satoru, Kim, Gon-Ho, Kirchen, Manuel, Klasky, Scott, Kline, John L, Krushelnick, Karl, Kustowski, Bogdan, Lapenta, Giovanni, Li, Wenting, Ma, Tammy, Mason, Nigel J, Mesbah, Ali, Michoski, Craig, Munson, Todd, Murakami, Izumi, Najm, Habib N, Olofsson, K. Erik J, Park, Seolhye, Peterson, J. Luc, Probst, Michael, Pugmire, David, Sammuli, Brian, Sawlani, Kapil, Scheinker, Alexander, Schissel, David P, Shalloo, Rob J, Shinagawa, Jun, Seong, Jaegu, Spears, Brian K, Tennyson, Jonathan, Thiagarajan, Jayaraman, Ticos, Catalin M, Trieschmann, Jan, van Dijk, Jan, Van Essen, Brian, Ventzek, Peter, Wang, Haimin, Wang, Jason T.L, Wang, Zhehui, Wende, Kristian, Xu, Xueqiao, Yamada, Hiroshi, Yokoyama, Tatsuya, Zhang, Xinhua

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Neural Network Surrogate Models for Absorptivity and Emissivity Spectra of Multiple Elements von Wal, Michael D. Vander, McClarren, Ryan G, Humbird, Kelli D

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Transfer Learning of High-Fidelity Opacity Spectra in Autoencoders and Surrogate Models von Vander Wal, Michael D, McClarren, Ryan G, Humbird, Kelli D

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Transfer Learning as a Method to Reproduce High-Fidelity NLTE Opacities in Simulations von Vander Wal, Michael D, McClarren, Ryan G, Humbird, Kelli D

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Adjoint-based Sensitivity Analysis for High-Energy Density Radiaitive Transfer using Flux-Limited Diffusion von Humbird, Kelli D, McClarren, Ryan G

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Neural Network Surrogate Models for Absorptivity and Emissivity Spectra of Multiple Elements von Vander Wal, Michael D, McClarren, Ryan G, Humbird, Kelli D

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