Pages that link to "Item:Q123703"

The following pages link to The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo (Q123703):

Displaying 50 items.

• ABC of the future (Q6089891) (← links)
• Adaptive weighting of Bayesian physics informed neural networks for multitask and multiscale forward and inverse problems (Q6095075) (← links)
• Probabilistic ordinal regression methods for multiple criteria sorting admitting certain and uncertain preferences (Q6096582) (← links)
• Efficient prediction of turbulent flow quantities using a Bayesian hierarchical multifidelity model (Q6101048) (← links)
• Bayesian inference under ramp stress accelerated life testing using Stan (Q6102205) (← links)
• Bivariate hierarchical Bayesian model for combining summary measures and their uncertainties from multiple sources (Q6104159) (← links)
• Using reference models in variable selection (Q6104420) (← links)
• Interpolating Population Distributions using Public-Use Data: An Application to Income Segregation using American Community Survey Data (Q6107192) (← links)
• Wavelet-\(L_2 E\) stochastic volatility models: an application to the water-energy nexus (Q6108884) (← links)
• Efficient data augmentation techniques for some classes of state space models (Q6111471) (← links)
• MCMC interweaving strategy for estimating stochastic volatility model and its application (Q6116260) (← links)
• Multilevel linear models, Gibbs samplers and multigrid decompositions (with discussion) (Q6117932) (← links)
• Surrogate-accelerated Bayesian framework for high-temperature thermal diffusivity characterization (Q6118511) (← links)
• \(R^{\ast}\): a robust MCMC convergence diagnostic with uncertainty using decision tree classifiers (Q6121679) (← links)
• Bayesian approximations to hidden semi-Markov models for telemetric monitoring of physical activity (Q6122037) (← links)
• Sequentially guided MCMC proposals for synthetic likelihoods and correlated synthetic likelihoods (Q6122057) (← links)
• Adaptive multi-stage integration schemes for Hamiltonian Monte Carlo (Q6129879) (← links)
• A Review of Data‐Driven Discovery for Dynamic Systems (Q6131430) (← links)
• Variational inference in neural functional prior using normalizing flows: application to differential equation and operator learning problems (Q6132292) (← links)
• Bayesian spatial quantile modeling applied to the incidence of extreme poverty in Lima-Peru (Q6136278) (← links)
• Longitudinal binary response models using alternative links for medical data (Q6137367) (← links)
• Bayesian inference and dynamic prediction for multivariate longitudinal and survival data (Q6138582) (← links)
• Modeling racial/ethnic differences in COVID-19 incidence with covariates subject to nonrandom missingness (Q6138597) (← links)
• On the accept-reject mechanism for Metropolis-Hastings algorithms (Q6139681) (← links)
• Flexible <i>cloglog</i> links for binomial regression models as an alternative for imbalanced medical data (Q6141308) (← links)
• Physics-informed information field theory for modeling physical systems with uncertainty quantification (Q6147081) (← links)
• CUQIpy: I. Computational uncertainty quantification for inverse problems in Python (Q6149901) (← links)
• CUQIpy: II. Computational uncertainty quantification for PDE-based inverse problems in Python (Q6149902) (← links)
• NeuralUQ: A Comprehensive Library for Uncertainty Quantification in Neural Differential Equations and Operators (Q6154538) (← links)
• Bayesian Deep Learning Framework for Uncertainty Quantification in Stochastic Partial Differential Equations (Q6154967) (← links)
• Scalable conditional deep inverse Rosenblatt transports using tensor trains and gradient-based dimension reduction (Q6158090) (← links)
• TensorBNN: Bayesian inference for neural networks using TensorFlow (Q6162824) (← links)
• A fully Bayesian sparse polynomial chaos expansion approach with joint priors on the coefficients and global selection of terms (Q6162876) (← links)
• Multilevel Delayed Acceptance MCMC (Q6164127) (← links)
• Convergence of unadjusted Hamiltonian Monte Carlo for mean-field models (Q6165984) (← links)
• Joint models for longitudinal and discrete survival data in credit scoring (Q6167389) (← links)
• Joint models of multivariate longitudinal outcomes and discrete survival data with INLA: an application to credit repayment behaviour (Q6168507) (← links)
• Intuitive joint priors for Bayesian linear multilevel models: the R2D2M2 prior (Q6170612) (← links)
• Nested sampling methods (Q6170637) (← links)
• Efficient and generalizable tuning strategies for stochastic gradient MCMC (Q6172924) (← links)
• Real-time mechanistic Bayesian forecasts of COVID-19 mortality (Q6179088) (← links)
• Bayesian estimation of multidimensional polytomous item response theory models with Q-matrices using Stan (Q6181869) (← links)
• Probabilistic physics-guided transfer learning for material property prediction in extrusion deposition additive manufacturing (Q6185217) (← links)
• Reversible Jump PDMP Samplers for Variable Selection (Q6185587) (← links)
• Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy (Q6185714) (← links)
• <scp>Mixture‐modelling‐based</scp> Bayesian <scp>MH‐RM</scp> algorithm for the multidimensional <scp>4PLM</scp> (Q6185853) (← links)
• Fully Bayesian Inference for Latent Variable Gaussian Process Models (Q6188699) (← links)
• Likelihood-free inference in state-space models with unknown dynamics (Q6190645) (← links)
• Randomized time Riemannian manifold Hamiltonian Monte Carlo (Q6190671) (← links)
• Gender inequalities at work in Southern Europe (Q6195482) (← links)