ArticlePhysical review applied2022
Simplified Algorithms for Adaptive Experiment Design in Parameter Estimation.
Article in Physical review applied, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- The Constrained Disorder Principle: A Paradigm Shift for Accurate Interactome Mapping and Information Analysis in Complex Biological Systems.Bioengineering (Basel, Switzerland) · 2025Review
- Weighing unequal parameter importance and measurement expense in adaptive quantum sensing.Journal of applied physics · 2025Article
- Bayesian active learning with model selection for spectral experiments.Scientific reports · 2024Article
- Capturing dynamical correlations using implicit neural representations.Nature communications · 2023Article
- Simplified Algorithms for Adaptive Experiment Design in Parameter Estimation.Physical review applied · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Measurements to estimate parameters of a model are commonplace in the physical sciences, where the traditional approach to automation is to use a sequence of preselected settings followed by least-squares fitting of a model function to the data. This measure-then-fit approach is simple and effective and entirely appropriate for many applications but when measurement resources are limited, efficiency becomes more important. To increase efficiency, Bayesian experiment design allows measurement settings to be chosen adaptively based on accumulated data and utility, the predicted improvement in results as a function of settings. However, the calculation of utility has been judged too impractical for most applications. In this paper, we introduce computational methods and simplified algorithms that accelerate utility calculations by over an order of magnitude, with only slight degradation in measurement efficiency. The methods eliminate utility calculation as a barrier to practical application of efficient adaptive measurement.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.