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Showing 1 to 8 of 8 for “"optimal experiment design"”.

  1. Automating Pareto-Optimal Experiment Design via Efficient Bayesian Optimization

    Many science, engineering, and design optimization problems require balancing the trade-offs between several conflicting objectives. The objectives are often blackbox functions whose evaluation requires time-consuming and costly experiments. Multi-objective Bayesian optimization can be used to …

    mit Repository record for Automating Pareto-Optimal Experiment Design via Efficient Bayesian Optimization (opens in a new tab)

  2. Multi-fidelity Optimal Trajectory Generation: Optimal Experiment Design for Robot Learning

    … dynamics. This thesis employs methods from optimal experiment design to address these challenges. By quantifying uncertainty and maximizing information gain, the approach aims to safely and efficiently design the real-world experiments required for accurate constraint modeling. In the first …

    mit Repository record for Multi-fidelity Optimal Trajectory Generation: Optimal Experiment Design for Robot Learning (opens in a new tab)

  3. Adjoint-accelerated Bayesian inference in thermoacoustics

    … Bayesian inference framework to assimilate experimental data into thermoacoustic models. The framework provides four main tools: (i) parameter inference, (ii) uncertainty quantification, (iii) model comparison, and (iv) optimal experiment design. With Bayesian parameter inference, we use …

    cambridge Repository record for Adjoint-accelerated Bayesian inference in thermoacoustics (opens in a new tab)

  4. Improving the identification of a penicillin fermentation model

    … genetic algorithms have been applied to the design of optimal experiments for model parameter estimation, and a new approach to assessing the theoretical identifiability of model structures has been proposed. When applied to the best penicillin fermentation model yet found, this new approach …

    birmingham Repository record for Improving the identification of a penicillin fermentation model (opens in a new tab)

  5. Automated Telescience: Active Machine Learning Of Remote Dynamical Systems

    … data to one that generates hypotheses and designs experiments. Despite the tremendous discoveries and advancements brought forth by the scientific method, it is a process that is fundamentally driven by human insight and ingenuity. Automated science aims to develop algorithms, protocols and …

    cornell Repository record for Automated Telescience: Active Machine Learning Of Remote Dynamical Systems (opens in a new tab)

  6. Multi-Input Multi-Output Repetitive Control Theory And Taylor Series Based Repetitive Control Design

    … the inverse system z-transfer function model to design Finite Impulse Response (FIR) repetitive controllers for single-input single-output (SISO) systems, and compares the designs obtained to those generated by optimization in the frequency domain. This approach is very simple, straightforward, …

    columbia-diss Repository record for Multi-Input Multi-Output Repetitive Control Theory And Taylor Series Based Repetitive Control Design (opens in a new tab)

  7. Quantitative Positron Emission Tomography for Estimation of Absolute Myocardial Blood Flow

    … clinical MPI. In this project, we investigated, designed and evaluated methods for MBF estimation that would enable a clinical protocol combining MPI and MBF.</p> <p>We focused on two aspects of the PET data. First, we characterized the adequacy of an existing clinical PET/CT scanner in providing …

    ohiolink Repository record for Quantitative Positron Emission Tomography for Estimation of Absolute Myocardial Blood Flow (opens in a new tab)