The following pages link to (Q3172405):
Displaying 50 items.
- Flexible Bayesian dynamic modeling of correlation and covariance matrices (Q2057355) (← links)
- Ensemble slice sampling. Parallel, black-box and gradient-free inference for correlated \& multimodal distributions (Q2058806) (← links)
- A spatial mixed-effects regression model for electoral data (Q2059109) (← links)
- A Bayesian approach for zero-modified Skellam model with Hamiltonian MCMC (Q2059119) (← links)
- A shared spatial model for multivariate extreme-valued binary data with non-random missingness (Q2061742) (← links)
- Statistical and deterministic inverse methods in the geosciences: introduction, review, and application to the nonlinear diffusion equation (Q2062363) (← links)
- Emulation-accelerated Hamiltonian Monte Carlo algorithms for parameter estimation and uncertainty quantification in differential equation models (Q2066738) (← links)
- Transfer of macroeconomic shocks in stress tests modeling (Q2067543) (← links)
- A hybrid scan Gibbs sampler for Bayesian models with latent variables (Q2075694) (← links)
- Optimal Bayesian smoothing of functional observations over a large graph (Q2078537) (← links)
- Bayesian inference for multistrain epidemics with application to \textit{Escherichia coli} O157:H7 in feedlot cattle (Q2078768) (← links)
- Estimating heterogeneous gene regulatory networks from zero-inflated single-cell expression data (Q2080734) (← links)
- Full Bayesian inference in hidden Markov models of plant growth (Q2080750) (← links)
- Variational inference for nonlinear inverse problems via neural net kernels: comparison to Bayesian neural networks, application to topology optimization (Q2083125) (← links)
- Mixing rates for Hamiltonian Monte Carlo algorithms in finite and infinite dimensions (Q2093317) (← links)
- Plateau proposal distributions for adaptive component-wise multiple-try metropolis (Q2098289) (← links)
- Fast Bayesian inference on spectral analysis of multivariate stationary time series (Q2101377) (← links)
- Bayesian learning via neural Schrödinger-Föllmer flows (Q2104005) (← links)
- Sticky PDMP samplers for sparse and local inference problems (Q2104011) (← links)
- Mixing time guarantees for unadjusted Hamiltonian Monte Carlo (Q2108472) (← links)
- Generalized integral transform and Hamiltonian Monte Carlo for Bayesian structural damage identification (Q2109785) (← links)
- MCMC-driven importance samplers (Q2110113) (← links)
- B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data (Q2123977) (← links)
- HMC: reducing the number of rejections by not using leapfrog and some results on the acceptance rate (Q2124354) (← links)
- Multi-fidelity Bayesian neural networks: algorithms and applications (Q2124403) (← links)
- Cauchy Markov random field priors for Bayesian inversion (Q2128078) (← links)
- Bayesian model inversion using stochastic spectral embedding (Q2131057) (← links)
- Hamiltonian Markov chain Monte Carlo for partitioned sample spaces with application to Bayesian deep neural nets (Q2131889) (← links)
- Bayesian inversion using adaptive polynomial chaos kriging within subset simulation (Q2133745) (← links)
- Bayesian mitigation of spatial coarsening for a Hawkes model applied to gunfire, wildfire and viral contagion (Q2135384) (← links)
- Oracle lower bounds for stochastic gradient sampling algorithms (Q2137007) (← links)
- Stochastic zeroth-order discretizations of Langevin diffusions for Bayesian inference (Q2137043) (← links)
- Stochastic gradient Hamiltonian Monte Carlo for non-convex learning (Q2137760) (← links)
- Pattern recognition in data as a diagnosis tool (Q2138195) (← links)
- Robust beta regression modeling with errors-in-variables: a Bayesian approach and numerical applications (Q2151693) (← links)
- Couplings for Andersen dynamics (Q2155520) (← links)
- Penalised t-walk MCMC (Q2156821) (← links)
- An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization (Q2159413) (← links)
- Variational inference with NoFAS: normalizing flow with adaptive surrogate for computationally expensive models (Q2162034) (← links)
- Challenges in Markov chain Monte Carlo for Bayesian neural networks (Q2163079) (← links)
- Parameters estimation in Ebola virus transmission dynamics model based on machine learning (Q2164308) (← links)
- Structured hierarchical models for probabilistic inference from perturbation screening data (Q2170453) (← links)
- Copula multivariate GARCH model with constrained Hamiltonian Monte Carlo (Q2178935) (← links)
- Estimating and forecasting the smoking-attributable mortality fraction for both genders jointly in over 60 countries (Q2179973) (← links)
- Non-linear failure rate: a Bayes study using Hamiltonian Monte Carlo simulation (Q2191253) (← links)
- Applying kriging proxies for Markov chain Monte Carlo in reservoir simulation (Q2192848) (← links)
- Markov chain Monte Carlo algorithms with sequential proposals (Q2209708) (← links)
- Localization for MCMC: sampling high-dimensional posterior distributions with local structure (Q2214525) (← links)
- Entropy-based closure for probabilistic learning on manifolds (Q2220629) (← links)
- GPU-accelerated particle methods for evaluation of sparse observations for inverse problems constrained by diffusion PDEs (Q2221390) (← links)
