Measurements with noise: Bayesian optimization for co-optimizing noise and property discovery in automated experiments Article Swipe
Boris N. Slautin
,
Yu Liu
,
J. Dec
,
Vladimir V. Shvartsman
,
Doru C. Lupascu
,
Maxim Ziatdinov
,
Sergei V. Kalinin
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1039/d4dd00391h
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1039/d4dd00391h
The proposed workflow integrates intra-step optimization into automated experiments, optimizing both the target property and measurement duration to enhance efficiency by balancing knowledge acquisition and experimental costs.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1039/d4dd00391h
- OA Status
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- Cited By
- 5
- References
- 36
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4408534627
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4408534627Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1039/d4dd00391hDigital Object Identifier
- Title
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Measurements with noise: Bayesian optimization for co-optimizing noise and property discovery in automated experimentsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-01-01Full publication date if available
- Authors
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Boris N. Slautin, Yu Liu, J. Dec, Vladimir V. Shvartsman, Doru C. Lupascu, Maxim Ziatdinov, Sergei V. KalininList of authors in order
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https://doi.org/10.1039/d4dd00391hPublisher landing page
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.1039/d4dd00391hDirect OA link when available
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Noise (video), Property (philosophy), Bayesian probability, Bayesian optimization, Computer science, Data mining, Artificial intelligence, Image (mathematics), Epistemology, PhilosophyTop concepts (fields/topics) attached by OpenAlex
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5Total citation count in OpenAlex
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2025: 5Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| primary_location.raw_type | journal-article |
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| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Digital Discovery |
| primary_location.landing_page_url | https://doi.org/10.1039/d4dd00391h |
| publication_date | 2025-01-01 |
| publication_year | 2025 |
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