# Full adaptation to smoothness using randomly truncated series priors with Gaussian coefficients and inverse gamma scaling

@article{Waaij2017FullAT, title={Full adaptation to smoothness using randomly truncated series priors with Gaussian coefficients and inverse gamma scaling}, author={Jan van Waaij and Harry van Zanten}, journal={Statistics \& Probability Letters}, year={2017}, volume={123}, pages={93-99} }

## 4 Citations

### Adaptive posterior contraction rates for empirical Bayesian drift estimation of a diffusion

- Mathematics
- 2019

Due to their conjugate posteriors, Gaussian process priors are attractive for estimating the drift of stochastic differential equations with continuous time observations. However, their performance…

### Adaptive posterior contraction rates for diffusions

- Mathematics
- 2018

Diffusions have many applications in science and can be described with a stochastic differential equation (SDE). We consider the following SDE, which was for example used in moleculair dynamics (see…

### Nonparametric Bayesian label prediction on a large graph using truncated Laplacian regularization

- Mathematics, Computer ScienceCommun. Stat. Simul. Comput.
- 2021

An implementation of a nonparametric Bayesian approach to solving binary classification problems on graphs with a prior constructed by truncating a series expansion of the soft label function using the graph Laplacian eigenfunctions as basisfunctions is described.

### Nonparametric Bayesian label prediction on a graph

- Computer Science, MathematicsComput. Stat. Data Anal.
- 2018

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