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A Practical Sequential Stopping Rule for High-Dimensional Markov Chain Monte Carlo
Taylor & Francis Verlag | 2016| -
Simultaneous Variable and Covariance Selection With the Multivariate Spike-and-Slab LASSO
Taylor & Francis Verlag | 2019| -
Efficient Implementations of the Generalized Lasso Dual Path Algorithm
Taylor & Francis Verlag | 2016| -
A Semiparametric Two-Sample Hypothesis Testing Problem for Random Graphs
Taylor & Francis Verlag | 2017| -
Optimally Adjusted Mixture Sampling and Locally Weighted Histogram Analysis
Taylor & Francis Verlag | 2017| -
A Metaheuristic Adaptive Cubature Based Algorithm to Find Bayesian Optimal Designs for Nonlinear Models
Taylor & Francis Verlag | 2019| -
Forward Event-Chain Monte Carlo: Fast Sampling by Randomness Control in Irreversible Markov Chains
Taylor & Francis Verlag | 2020| -
Efficient Sampling for Gaussian Linear Regression With Arbitrary Priors
Taylor & Francis Verlag | 2019| -
Gaussian Variational Approximation With a Factor Covariance Structure
Taylor & Francis Verlag | 2018| -
Toward Automatic Model Comparison: An Adaptive Sequential Monte Carlo Approach
Free accessTaylor & Francis Verlag | 2016| -
Fast Algorithms for Large-Scale Generalized Distance Weighted Discrimination
Taylor & Francis Verlag | 2018| -
Identifying Mixtures of Mixtures Using Bayesian Estimation
Free accessTaylor & Francis Verlag | 2017|
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