Pages that link to "Item:Q2375191"
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The following pages link to Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction (Q2375191):
Displaying 38 items.
- Special issue: Big data and predictive computational modeling (Q727038) (← links)
- Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the antarctic ice sheet (Q727759) (← links)
- Data-driven combined state and parameter reduction for inverse problems (Q904256) (← links)
- Multimodal, high-dimensional, model-based, Bayesian inverse problems with applications in biomechanics (Q1714421) (← links)
- Deep composition of tensor-trains using squared inverse Rosenblatt transports (Q2098237) (← links)
- Forward and backward uncertainty quantification with active subspaces: application to hypersonic flows around a cylinder (Q2122694) (← links)
- Fast Bayesian inversion for high dimensional inverse problems (Q2128074) (← links)
- Variational Bayesian approximation of inverse problems using sparse precision matrices (Q2138759) (← links)
- Rate-optimal refinement strategies for local approximation MCMC (Q2172107) (← links)
- Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance (Q2196543) (← links)
- Localization for MCMC: sampling high-dimensional posterior distributions with local structure (Q2214525) (← links)
- Adaptive multi-fidelity polynomial chaos approach to Bayesian inference in inverse problems (Q2214560) (← links)
- Demonstration of the relationship between sensitivity and identifiability for inverse uncertainty quantification (Q2222401) (← links)
- Bayesian inference of heterogeneous epidemic models: application to COVID-19 spread accounting for long-term care facilities (Q2237746) (← links)
- On dimension reduction in Gaussian filters (Q2806026) (← links)
- MALA-within-Gibbs Samplers for High-Dimensional Distributions with Sparse Conditional Structure (Q3300855) (← links)
- Iterative Importance Sampling Algorithms for Parameter Estimation (Q4607633) (← links)
- Parallel Local Approximation MCMC for Expensive Models (Q4636376) (← links)
- Multifidelity Approximate Bayesian Computation (Q4960985) (← links)
- Stein Variational Reduced Basis Bayesian Inversion (Q4997362) (← links)
- Prior normalization for certified likelihood-informed subspace detection of Bayesian inverse problems (Q5044972) (← links)
- Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments (Q5071443) (← links)
- Certified dimension reduction in nonlinear Bayesian inverse problems (Q5082037) (← links)
- Multifidelity Dimension Reduction via Active Subspaces (Q5107797) (← links)
- Scalable Optimization-Based Sampling on Function Space (Q5112552) (← links)
- Bayesian Probabilistic Numerical Methods in Time-Dependent State Estimation for Industrial Hydrocyclone Equipment (Q5208054) (← links)
- Non‐linear model reduction for uncertainty quantification in large‐scale inverse problems (Q5306460) (← links)
- Numerical linear algebra in data assimilation (Q6068266) (← links)
- Certified Dimension Reduction for Bayesian Updating with the Cross-Entropy Method (Q6109169) (← links)
- A greedy sensor selection algorithm for hyperparameterized linear Bayesian inverse problems with correlated noise models (Q6146995) (← links)
- Scalable conditional deep inverse Rosenblatt transports using tensor trains and gradient-based dimension reduction (Q6158090) (← links)
- Deep Importance Sampling Using Tensor Trains with Application to a Priori and a Posteriori Rare Events (Q6189161) (← links)
- Multilevel dimension-independent likelihood-informed MCMC for large-scale inverse problems (Q6194963) (← links)
- A MCMC method based on surrogate model and Gaussian process parameterization for infinite Bayesian PDE inversion (Q6553787) (← links)
- Learning to solve Bayesian inverse problems: an amortized variational inference approach using Gaussian and flow guides (Q6560691) (← links)
- hIPPYlib-MUQ: a Bayesian inference software framework for integration of data with complex predictive models under uncertainty (Q6601373) (← links)
- Deep adaptive sampling for surrogate modeling without labeled data (Q6639518) (← links)
- Adaptive operator learning for infinite-dimensional Bayesian inverse problems (Q6669407) (← links)
