Hauptseite > Publikationsdatenbank > Diploma Best Paper Award: 15th lnternational Conference on Parallel Processing and Applied Mathematics (PPAM 2024) > print |
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037 | _ | _ | |a FZJ-2024-05793 |
100 | 1 | _ | |0 P:(DE-Juel1)177985 |a Rüttgers, Mario |b 0 |u fzj |
245 | _ | _ | |a Diploma Best Paper Award: 15th lnternational Conference on Parallel Processing and Applied Mathematics (PPAM 2024) |
260 | _ | _ | |b PPAM 2024 Chairs of Program Committee |
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336 | 7 | _ | |0 PUB:(DE-HGF)38 |2 PUB:(DE-HGF) |a Award |b award |m award |s 1730972424_30533 |
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502 | _ | _ | |d 2024 |
520 | _ | _ | |a DIPLOMA: PPAM Besf Paper Award. The lnternational Conference on Parallel Processing and Applied Mathematics (PPAM) Best Paper Award is given upon recommendation of the PPAM Chairs and Program Committee in recognition of the research paper's quality, originality, and significance of the work in high performance computing. The PPAM Best Paper was first awarded at PPAM 2019 in Bialystok. The PPAM 2024 Award for Workshop is bestowed to: Mario Rüttgers, Fabian Hübenthal, Makoto Tsubokura, and Andreas Lintermann for their paper "Parallel reinforcement learning and Gaussian process regress for improved physics-based nasal surgery planning". |
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536 | _ | _ | |0 G:(EU-Grant)101136269 |a HANAMI - Hpc AlliaNce for Applications and supercoMputing Innovation: the Europe - Japan collaboration (101136269) |c 101136269 |x 1 |
700 | 1 | _ | |0 P:(DE-HGF)0 |a Hübenthal, Fabian |b 1 |
700 | 1 | _ | |0 P:(DE-HGF)0 |a Tsubokura, Makoto |b 2 |
700 | 1 | _ | |0 P:(DE-Juel1)165948 |a Lintermann, Andreas |b 3 |u fzj |
856 | 4 | _ | |u https://ppam.edu.pl |
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