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Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing.

, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , и . SMC, том 1512 из Communications in Computer and Information Science, стр. 361-382. Springer, (2021)

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Julij Kalinin

Sergei Traustel

Sergei Traustel

Sergei Adichtchev

Sergei Sawitzki

 

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Tunable metallic conductance in ferroelectric nanodomains, , , , , , , и . Nano letters, 12 (1): 209--213 (2011)Anisotropic conductivity of uncharged domain walls in BiFeO 3, , , , и . Physical Review B, 86 (8): 085315 (2012)Estimating Preisach Density via Subset Selection., , , , и . IEEE Access, (2020)Unraveling the Impact of Initial Choices and In-Loop Interventions on Learning Dynamics in Autonomous Scanning Probe Microscopy., , , и . CoRR, (2024)Human-in-the-loop: The future of Machine Learning in Automated Electron Microscopy., , , , , , , и . CoRR, (2023)Co-orchestration of Multiple Instruments to Uncover Structure-Property Relationships in Combinatorial Libraries., , , , , , , , и . CoRR, (2024)Semi-supervised learning of images with strong rotational disorder: assembling nanoparticle libraries., , , , и . CoRR, (2021)Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders *., , и . Mach. Learn. Sci. Technol., 4 (4): 45033 (декабря 2023)Combining variational autoencoders and physical bias for improved microscopy data analysis ∗., , и . Mach. Learn. Sci. Technol., 4 (4): 45004 (декабря 2023)Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery., , , , , , , , , и 3 other автор(ы). SMC, том 1512 из Communications in Computer and Information Science, стр. 58-75. Springer, (2021)