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SoK: Understanding Design Choices and Pitfalls of Trusted Execution Environments

• Authors : Li, Mengyuan; Yang, Yuheng; Chen, Guoxing

• Source: Association for Computing Machinery

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Machine learning approaches reveal highly heterogeneous air quality co-benefits of the energy transition

• Authors : Zhang, Da; Wang, Qingyi; Song, Shaojie

• Source: Elsevier

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Portable performance on heterogeneous architectures

• Authors : Phothilimthana, Phitchaya Mangpo; Ansel, Jason Andrew; Ragan-Kelley, Jonathan Millar ...

• Source: MIT web domain

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Monkey: A Distributed Orchestrator for a Virtual Pseudo-Homogenous Computational Cluster Consisting of Heterogeneous Sources

• Authors : Stallone, Matthew J.;

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Fast group matching for MR fingerprinting reconstruction

• Authors : Cauley, Stephen F.; Setsompop, Kawin; Ma, Dan ...

• Source: PMC

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Human-Informed Topology Optimization: interactive application of feature size controls

• Authors : Ha, Dat Q.; Carstensen, Josephine V.; Massachusetts Institute of Technology. Department of Civil and Environmental Engineering

• Source: Springer Berlin Heidelberg

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Computational techniques for the analysis of small signals in high-statistics neutrino oscillation experiments

• Source: arXiv

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Significant Sampling for Shortest Path Routing: A Deep Reinforcement Learning Solution

• Authors : Shao, Yulin; Rezaee, Arman; Liew, Soung Chang ...

• Source: Prof. Chan via Phoebe Ayers

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Computational techniques for the analysis of small signals in high-statistics neutrino oscillation experiments

• Authors : Arguelles Delgado, Carlos A; Axani, Spencer Nicholas; Collin, G. H. ...

• Source: arXiv

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Guidance for Closed-Loop Transfers using Reinforcement Learning with Application to Libration Point Orbits

• Authors : LaFarge, Nicholas B; Miller, Daniel; Howell, Kathleen C ...

• Source: MIT web domain

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