Pages that link to "Item:Q1596095"
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The following pages link to Bayesian experimental design: A review (Q1596095):
Displaying 50 items.
- Gaussian Process Landmarking on Manifolds (Q5025781) (← links)
- Unbiased MLMC Stochastic Gradient-Based Optimization of Bayesian Experimental Designs (Q5028414) (← links)
- Combustion kinetic model development using surrogate model similarity method (Q5032130) (← links)
- Quantum-state estimation problem via optimal design of experiments (Q5037884) (← links)
- (Q5053276) (← links)
- Adaptive Test Allocation for Outbreak Detection and Tracking in Social Contact Networks (Q5073508) (← links)
- Design analysis for optimal calibration of diffusivity in reactive multilayers (Q5073610) (← links)
- Varying Coefficient Models and Design Choice for Bayes Linear Emulation of Complex Computer Models with Limited Model Evaluations (Q5075228) (← links)
- Bayesian optimum accelerated life test plans based on quantile regression (Q5088123) (← links)
- Risk-Adapted Optimal Experimental Design (Q5097842) (← links)
- Optimal Experimental Design for Inverse Problems in the Presence of Observation Correlations (Q5101014) (← links)
- The Bayesian D-optimal design for simple beta regression model in two cases (both known and unknown nuisance parameter) (Q5106848) (← links)
- Bayesian Optimal Design for Ordinary Differential Equation Models With Application in Biological Science (Q5130598) (← links)
- (Q5134646) (← links)
- (Q5134834) (← links)
- Bayesian<i>D</i>-optimal Accelerated Life Test plans for series systems with competing exponential causes of failure (Q5138096) (← links)
- An Information Criterion for Choosing Observation Locations in Data Assimilation and Prediction (Q5149776) (← links)
- Optimal Design of Large-scale Bayesian Linear Inverse Problems Under Reducible Model Uncertainty: Good to Know What You Don't Know (Q5149782) (← links)
- Dethroning the Fano Factor: A Flexible, Model-Based Approach to Partitioning Neural Variability (Q5157158) (← links)
- On sample size determination based on a Bayesian index of superiority for two independent binomial proportions (Q5193383) (← links)
- <i>K</i>-Optimal Design via Semidefinite Programming and Entropy Optimization (Q5252232) (← links)
- Efficient Bayesian Experimentation Using an Expected Information Gain Lower Bound (Q5269853) (← links)
- A-optimal encoding weights for nonlinear inverse problems, with application to the Helmholtz inverse problem (Q5348010) (← links)
- Bayesian Active Learning of Neural Firing Rate Maps with Transformed Gaussian Process Priors (Q5383788) (← links)
- Bayesian Experimental Design for Models with Intractable Likelihoods (Q5408014) (← links)
- Bayesian and maximin optimal designs for heteroscedastic regression models (Q5696345) (← links)
- Inverse Heat Source Problem and Experimental Design for Determining Iron Loss Distribution (Q5857632) (← links)
- Edge-Promoting Adaptive Bayesian Experimental Design for X-ray Imaging (Q5864076) (← links)
- An Offline-Online Decomposition Method for Efficient Linear Bayesian Goal-Oriented Optimal Experimental Design: Application to Optimal Sensor Placement (Q5886849) (← links)
- Locally D-Optimal Designs for Hierarchical Response Experiments (Q6039881) (← links)
- D‐optimal designs for a continuous predictor in longitudinal trials with discrete‐time survival endpoints (Q6063617) (← links)
- Finding Bayesian Optimal Designs for Nonlinear Models: A Semidefinite Programming‐Based Approach (Q6064606) (← links)
- A Review of Modern Computational Algorithms for Bayesian Optimal Design (Q6064627) (← links)
- Bayesian subcohort selection for longitudinal covariate measurements in follow‐up studies (Q6068046) (← links)
- Joint control of consensus and evidence in Bayesian design of clinical trials (Q6068807) (← links)
- Optimization of sampling designs for pedigrees and association studies (Q6079587) (← links)
- Adaptive and robust experimental design for linear dynamical models using Kalman filter (Q6080697) (← links)
- Bayesian sequential optimal experimental design for nonlinear models using policy gradient reinforcement learning (Q6084438) (← links)
- Sequential experiment design for parameter estimation of nonlinear systems using a neural network approximator (Q6092474) (← links)
- Bayesian experimental design without posterior calculations: an adversarial approach (Q6122019) (← links)
- Multifidelity Bayesian Experimental Design to Quantify Rare-Event Statistics (Q6131420) (← links)
- Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter (Q6159325) (← links)
- Bayesian and maximin optimal designs for heteroscedastic multi-factor regression models (Q6201373) (← links)
- Bayesian decision-theoretic design of experiments under an alternative model (Q6203241) (← links)
- Optimal sample planning for system state analysis with partial data collection (Q6538489) (← links)
- Modern Bayesian experimental design (Q6540235) (← links)
- Optimal Bayesian experimental design for priors of compact support with application to shock-tube experiments for combustion kinetics (Q6560675) (← links)
- Statistical methods in experimentation recommendation models for discovering gene regulation pathways (Q6562688) (← links)
- Discussion of: ``Methods for planning repeated measures accelerated degradation tests'' (Q6571872) (← links)
- Adaptive data collection for intraindividual studies affected by adherence (Q6572285) (← links)
