The following pages link to Bayesian Compressive Sensing (Q4568729):
Displaying 50 items.
- Off-grid DOA estimation via real-valued sparse Bayesian method in compressed sensing (Q318224) (← links)
- Ensemble extreme learning machine and sparse representation classification (Q344642) (← links)
- Selection of polynomial chaos bases via Bayesian model uncertainty methods with applications to sparse approximation of PDEs with stochastic inputs (Q348681) (← links)
- A weighted \(\ell_1\)-minimization approach for sparse polynomial chaos expansions (Q349012) (← links)
- Sparse microwave imaging: principles and applications (Q362310) (← links)
- Nonconvex compressed sampling of natural images and applications to compressed MR imaging (Q408496) (← links)
- Convex feasibility modeling and projection methods for sparse signal recovery (Q442713) (← links)
- Expectation propagation in linear regression models with spike-and-slab priors (Q493741) (← links)
- Regression analysis of locality preserving projections via sparse penalty (Q528758) (← links)
- A Bayesian mixed shrinkage prior procedure for spatial-stochastic basis selection and evaluation of gPC expansions: applications to elliptic SPDEs (Q729029) (← links)
- Sparsity preserving projections with applications to face recognition (Q733184) (← links)
- Sparse polynomial chaos expansions using variational relevance vector machines (Q781971) (← links)
- From compression to compressed sensing (Q905909) (← links)
- Compressive sensing for multi-static scattering analysis (Q1017608) (← links)
- Landmark recognition with sparse representation classification and extreme learning machine (Q1660684) (← links)
- Large-scale hyperspectral image compression via sparse representations based on online learning (Q1787085) (← links)
- \(\ell_1\)- and \(\ell_2\)-norm joint regularization based sparse signal reconstruction scheme (Q1793017) (← links)
- Image restoration via simultaneous sparse coding: where structured sparsity meets Gaussian scale mixture (Q1799981) (← links)
- Sparse signal recovery via ECME thresholding pursuits (Q1954822) (← links)
- An efficient and robust adaptive sampling method for polynomial chaos expansion in sparse Bayesian learning framework (Q1988073) (← links)
- Sequential sparse Bayesian learning with applications to system identification for damage assessment and recursive reconstruction of image sequences (Q2020862) (← links)
- Accelerating the Bayesian inference of inverse problems by using data-driven compressive sensing method based on proper orthogonal decomposition (Q2055173) (← links)
- Learning to scan: a deep reinforcement learning approach for personalized scanning in CT imaging (Q2072167) (← links)
- Feasibility of DEIM for retrieving the initial field via dimensionality reduction (Q2120024) (← links)
- SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations (Q2128325) (← links)
- Sparse Bayesian learning for network structure reconstruction based on evolutionary game data (Q2137626) (← links)
- Sequential image recovery from noisy and under-sampled Fourier data (Q2149043) (← links)
- Sparse signal recovery via generalized Gaussian function (Q2154451) (← links)
- A neurodynamic approach to nonlinear optimization problems with affine equality and convex inequality constraints (Q2182907) (← links)
- Cluster sparsity field: an internal hyperspectral imagery prior for reconstruction (Q2200022) (← links)
- Compressive sensing adaptation for polynomial chaos expansions (Q2214527) (← links)
- Optimal observations-based retrieval of topography in 2D shallow water equations using PC-EnKF (Q2214574) (← links)
- Hyper-Laplacian regularized nonlocal low-rank matrix recovery for hyperspectral image compressive sensing reconstruction (Q2224828) (← links)
- Statistical interpolation of spatially varying but sparsely measured 3D geo-data using compressive sensing and variational Bayesian inference (Q2238104) (← links)
- Variance-based adaptive sequential sampling for polynomial chaos expansion (Q2246308) (← links)
- A hybrid sequential sampling strategy for sparse polynomial chaos expansion based on compressive sampling and Bayesian experimental design (Q2246331) (← links)
- Detecting edges from non-uniform Fourier data via sparse Bayesian learning (Q2316239) (← links)
- Global sensitivity analysis based on high-dimensional sparse surrogate construction (Q2363869) (← links)
- An Overview of Computational Sparse Models and Their Applications in Artificial Intelligence (Q2866116) (← links)
- A Bayesian Meta-Modeling Approach for Gaussian Stochastic Process Models Using a Non Informative Prior (Q2884884) (← links)
- CURVELET-WAVELET REGULARIZED SPLIT BREGMAN ITERATION FOR COMPRESSED SENSING (Q3084700) (← links)
- Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions (Q3176252) (← links)
- Temporal Compressive Sensing for Video (Q3460829) (← links)
- Optimization Methods for Synthetic Aperture Radar Imaging (Q4556980) (← links)
- Sparsity Constrained Estimation in Image Processing and Computer Vision (Q4556987) (← links)
- Task-Driven Adaptive Statistical Compressive Sensing of Gaussian Mixture Models (Q4578376) (← links)
- On the local and global minimizers of $ \newcommand{\e}{{\rm e}} \ell_0$ gradient regularized model with box constraints for image restoration (Q4582667) (← links)
- Fast Bayesian JPEG Decompression and Denoising With Tight Frame Priors (Q4618574) (← links)
- Bayesian adaptation of chaos representations using variational inference and sampling on geodesics (Q4626133) (← links)
- Robust data-driven discovery of governing physical laws with error bars (Q4626135) (← links)
