18 citations · 65 across the 9 of their papers we have counts for
6 papers · 1 filter
Lagrangian Manifold Monte Carlo on Monge Patches
Marcelo Hartmann, Mark Girolami, Arto Klami
The efficiency of Markov Chain Monte Carlo (MCMC) depends on how the underlying geometry of the problem is taken into account. For distributions with strongly varying curvature, Ri…
Prior knowledge elicitation: The past, present, and future
Petrus Mikkola, Osvaldo A. Martin, Suyog Chandramouli +9
Specification of the prior distribution for a Bayesian model is a central part of the Bayesian workflow for data analysis, but it is often difficult even for statistical experts. I…
Flexible Prior Elicitation via the Prior Predictive Distribution
Marcelo Hartmann, Georgi Agiashvili, Paul Bürkner +1
The prior distribution for the unknown model parameters plays a crucial role in the process of statistical inference based on Bayesian methods. However, specifying suitable priors…
Additive multivariate Gaussian processes for joint species distribution modeling with heterogeneous data
Jarno Vanhatalo, Marcelo Hartmann, Lari Veneranta
Species distribution models (SDM) are a key tool in ecology, conservation and management of natural resources. Two key components of the state-of-the-art SDMs are the description f…
Laplace approximation and the natural gradient for Gaussian process regression with the heteroscedastic Student-t model
Marcelo Hartmann, Jarno Vanhatalo
This paper considers the Laplace method to derive approximate inference for the Gaussian process (GP) regression in the location and scale parameters of the Student-t probabilistic…
Extending Owen's integral table and a new multivariate Bernoulli distribution
Marcelo Hartmann
We extend some equatilites in the Owen's table of normal integrals (A table of normal integrals in Communication in Statistics-Simulation and Computation, 1980). Furthermore a new…