
Statistical Guarantees and Algorithmic Convergence Issues of Variational Boosting
We provide statistical guarantees for Bayesian variational boosting by p...
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Evidence bounds in singular models: probabilistic and variational perspectives
The marginal likelihood or evidence in Bayesian statistics contains an i...
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Dynamics of coordinate ascent variational inference: A case study in 2D Ising models
Variational algorithms have gained prominence over the past two decades ...
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Continuous shrinkage prior revisited: a collapsing behavior and remedy
Modern genomic studies are increasingly focused on identifying more and ...
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Nonasymptotic Laplace approximation under model misspecification
We present nonasymptotic twosided bounds to the logmarginal likelihoo...
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On truncated multivariate normal priors in constrained parameter spaces
We show that any lowerdimensional marginal density obtained from trunca...
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Bayesian Copula Density Deconvolution for ZeroInflated Data in Nutritional Epidemiology
Estimating the marginal and joint densities of the longterm average int...
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Gaussian Processes with Errors in Variables: Theory and Computation
Covariate measurement error in nonparametric regression is a common prob...
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Efficient Bayesian shaperestricted function estimation with constrained Gaussian process priors
This article revisits the problem of Bayesian shaperestricted inference...
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Bayesian Graph Selection Consistency For Decomposable Graphs
Gaussian graphical models are a popular tool to learn the dependence str...
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Bayesian Hierarchical Modeling on Covariance Valued Data
Analysis of structural and functional connectivity (FC) of human brains ...
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Revisiting the protonradius problem using constrained Gaussian processes
Background: The "proton radius puzzle" refers to an eightyear old probl...
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The Soft Multivariate Truncated Normal Distribution
We propose a new distribution, called the soft tMVN distribution, which ...
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ShapeConstrained Univariate Density Estimation
While the problem of estimating a probability density function (pdf) fro...
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On Statistical Optimality of Variational Bayes
The article addresses a longstanding open problem on the justification ...
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αVariational Inference with Statistical Guarantees
We propose a variational approximation to Bayesian posterior distributio...
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Frequentist coverage and supnorm convergence rate in Gaussian process regression
Gaussian process (GP) regression is a powerful interpolation technique d...
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Bayesian model selection consistency and oracle inequality with intractable marginal likelihood
In this article, we investigate large sample properties of model selecti...
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Sparse additive Gaussian process with soft interactions
Additive nonparametric regression models provide an attractive tool for ...
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Bayesian Clustering of Shapes of Curves
Unsupervised clustering of curves according to their shapes is an import...
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Debdeep Pati
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