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08/16/2023
Warped geometric information on the optimisation of Euclidean functions
We consider the fundamental task of optimizing a real-valued function de...
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03/09/2023
Scalable Stochastic Gradient Riemannian Langevin Dynamics in Non-Diagonal Metrics
Stochastic-gradient sampling methods are often used to perform Bayesian ...
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02/01/2022
Lagrangian Manifold Monte Carlo on Monge Patches
The efficiency of Markov Chain Monte Carlo (MCMC) depends on how the und...
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12/01/2021
Prior knowledge elicitation: The past, present, and future
Specification of the prior distribution for a Bayesian model is a centra...
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02/23/2020
Flexible Prior Elicitation via the Prior Predictive Distribution
The prior distribution for the unknown model parameters plays a crucial ...
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10/27/2019
Prior specification via prior predictive matching: Poisson matrix factorization and beyond
Hyperparameter optimization for machine learning models is typically car...
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09/07/2018
Joint species distribution modeling with additive multivariate Gaussian process priors and heteregenous data
In this work, we propose JSDMs where the responses to environmental cova...
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12/20/2017