Thorsten Kurth
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
13
Venues
3
Active years
2016–2024
Best venue rank
A*
Where they publish
Papers
13 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | ICML | Neural Operators with Localized Integral and Differential Kernels. | Miguel Liu-Schiaffini, Julius Berner, Boris Bonev, Thorsten Kurth, Kamyar Azizzadenesheli, Anima Anandkumar |
| 2024 | SC | Toward Capturing Genetic Epistasis From Multivariate Genome-Wide Association Studies Using Mixed-Precision Kernel Ridge Regression. | Hatem Ltaief, Rabab Alomairy, Qinglei Cao, Jie Ren, Lotfi Slim, Thorsten Kurth, Benedikt Dorschner, Salim Bougouffa, Rached Abdelkhalak, David E. Keyes |
| 2023 | ICML | Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere. | Boris Bonev, Thorsten Kurth, Christian Hundt, Jaideep Pathak, Maximilian Baust, Karthik Kashinath, Anima Anandkumar |
| 2021 | ICPP | IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads. | Aymen Al Saadi, Dario Alf, Yadu N. Babuji, Agastya Bhati, Ben Blaiszik, Alexander Brace, Thomas S. Brettin, Kyle Chard, Ryan Chard, Austin Clyde, Peter V. Coveney, Ian T. Foster, Tom Gibbs, Shantenu Jha, Kristopher Keipert, Dieter Kranzlmller, Thorsten Kurth, Hyungro Lee, Zhuozhao Li, Heng Ma, Gerald Mathias, Andr Merzky, Alexander Partin, Arvind Ramanathan, Ashka Shah, Abraham C. Stern, Rick Stevens, Li Tan, Mikhail Titov, Anda Trifan, Aristeidis Tsaris, Matteo Turilli, Huub J. J. Van Dam, Shunzhou Wan, David Wifling, Junqi Yin |
| 2020 | SC | Time-Based Roofline for Deep Learning Performance Analysis. | Yunsong Wang, Charlene Yang, Steven Farrell, Yan Zhang, Thorsten Kurth, Samuel Williams |
| 2019 | SC | Performance Portability of a Wilson Dslash Stencil Operator Mini-App Using Kokkos and SYCL. | Blint Jo, Thorsten Kurth, Michael A. Clark, Jeongnim Kim, Christian Robert Trott, Dan Ibanez, Daniel Sunderland, Jack Deslippe |
| 2019 | SC | Highly-Ccalable, Physics-Informed GANs for Learning Solutions of Stochastic PDEs. | Liu Yang, Prabhat, George E. Karniadakis, Sean Treichler, Thorsten Kurth, Keno Fischer, David A. Barajas-Solano, Joshua Romero, Valentin Churavy, Alexandre M. Tartakovsky, Michael Houston |
| 2018 | SC | A Metric for Evaluating Supercomputer Performance in the Era of Extreme Heterogeneity. | Brian Austin, Christopher S. Daley, Douglas Doerfler, Jack Deslippe, Brandon Cook, Brian Friesen, Thorsten Kurth, Charlene Yang, Nicholas J. Wright |
| 2018 | SC | Simulating the | Evan Berkowitz, Michael A. Clark, Arjun Singh Gambhir, Kenneth McElvain, Amy N. Nicholson, Enrico Rinaldi, Pavlos Vranas, Andr Walker-Loud, Chia-Cheng Chang, Blint Jo, Thorsten Kurth, Kostas Orginos |
| 2018 | SC | A Case Study for Performance Portability Using OpenMP 4.5. | Rahulkumar Gayatri, Charlene Yang, Thorsten Kurth, Jack Deslippe |
| 2018 | SC | Exascale deep learning for climate analytics. | Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael A. Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston |
| 2017 | SC | Deep learning at 15PF: supervised and semi-supervised classification for scientific data. | Thorsten Kurth, Jian Zhang, Nadathur Satish, Evan Racah, Ioannis Mitliagkas, Md. Mostofa Ali Patwary, Tareq M. Malas, Narayanan Sundaram, Wahid Bhimji, Mikhail Smorkalov, Jack Deslippe, Mikhail Shiryaev, Srinivas Sridharan, Prabhat, Pradeep Dubey |
| 2016 | SC | Evaluating and Optimizing the NERSC Workload on Knights Landing. | Taylor Barnes, Brandon Cook, Jack Deslippe, Douglas Doerfler, Brian Friesen, Yun (Helen) He, Thorsten Kurth, Tuomas Koskela, Mathieu Lobet, Tareq M. Malas, Leonid Oliker, Andrey Ovsyannikov, Abhinav Sarje, Jean-Luc Vay, Henri Vincenti, Samuel Williams, Pierre Carrier, Nathan Wichmann, Marcus Wagner, Paul R. C. Kent, Christopher Kerr, John M. Dennis |