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Deep-Hurricane-Tracker: Tracking and Forecasting Extreme Climate Events., , , , , , и . WACV, стр. 1761-1769. IEEE, (2019)Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist., , , , , , , , и . KDD, стр. 293-301. ACM, (2018)DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems., , , , , , , , , и 1 other автор(ы). MLHPC@SC, стр. 75-87. IEEE, (2019)Techniques for modeling large-scale HPC I/O workloads., , , , , , , , , и . PMBS@SC, стр. 5:1-5:11. ACM, (2015)Taming parallel I/O complexity with auto-tuning., , , , , , , и . SC, стр. 68:1-68:12. ACM, (2013)Data Elevator: Low-Contention Data Movement in Hierarchical Storage System., , , , , , и . HiPC, стр. 152-161. IEEE Computer Society, (2016)Evaluation of HPC Application I/O on Object Storage Systems., , , , , , , , , и 2 other автор(ы). PDSW-DISCS@SC, стр. 24-34. IEEE, (2018)Interactive Distributed Deep Learning with Jupyter Notebooks., , , , , , , , , и . ISC Workshops, том 11203 из Lecture Notes in Computer Science, стр. 678-687. Springer, (2018)Dynamic Model-Driven Parallel I/O Performance Tuning., , , , и . CLUSTER, стр. 184-193. IEEE Computer Society, (2015)Celeste: Variational inference for a generative model of astronomical images., , , , , , , и . ICML, том 37 из JMLR Workshop and Conference Proceedings, стр. 2095-2103. JMLR.org, (2015)