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Concept-Driven Visual Analytics: an Exploratory Study of Model- and Hypothesis-Based Reasoning with Visualizations., , , , , and . CHI, page 68. ACM, (2019)Fine-Grained Processing Towards HL-LHC Computing in ATLAS., , , , , , , , , and 6 other author(s). eScience, page 338. IEEE Computer Society, (2018)Machine Learning in High Energy Physics Community White Paper., , , , , , , , , and 108 other author(s). CoRR, (2018)Evaluating Portable Parallelization Strategies for Heterogeneous Architectures in High Energy Physics., , , , , , , , , and 10 other author(s). CoRR, (2023)Deep Reinforcement Agent for Scheduling in HPC., , , , , and . IPDPS, page 807-816. IEEE, (2021)DRAS: Deep Reinforcement Learning for Cluster Scheduling in High Performance Computing., , , , , , , , and . IEEE Trans. Parallel Distributed Syst., 33 (12): 4903-4917 (2022)Developments in Performance and Portability for MadGraph5_aMC@NLO., , , , , , , , and . CoRR, (2022)Balsam: Automated Scheduling and Execution of Dynamic, Data-Intensive HPC Workflows., , , , , and . CoRR, (2019)Toward Real-time Analysis of Experimental Science Workloads on Geographically Distributed Supercomputers., , , , and . CoRR, (2021)Improving Performance Portability of the Procedurally Generated High Energy Physics Event Generator MadGraph Using SYCL., , , and . IWOCL, page 8:1-8:8. ACM, (2024)