2 citations · 3 across the 3 of their papers we have counts for
4 papers
Streaming Bayes GFlowNets
Tiago da Silva, Daniel Augusto de Souza, Diego Mesquita
Bayes' rule naturally allows for inference refinement in a streaming fashion, without the need to recompute posteriors from scratch whenever new data arrives. In principle, Bayesia…
Parallel MCMC Without Embarrassing Failures
Daniel Augusto de Souza, Diego Mesquita, Samuel Kaski +1
Embarrassingly parallel Markov Chain Monte Carlo (MCMC) exploits parallel computing to scale Bayesian inference to large datasets by using a two-step approach. First, MCMC is run i…
No-PASt-BO: Normalized Portfolio Allocation Strategy for Bayesian Optimization
Thiago de P. Vasconcelos, Daniel A. R. M. A. de Souza, César L. C. Mattos +1
Bayesian Optimization (BO) is a framework for black-box optimization that is especially suitable for expensive cost functions. Among the main parts of a BO algorithm, the acquisiti…
Learning GPLVM with arbitrary kernels using the unscented transformation
Daniel Augusto R. M. A. de Souza, Diego Mesquita, César Lincoln C. Mattos +1
Gaussian Process Latent Variable Model (GPLVM) is a flexible framework to handle uncertain inputs in Gaussian Processes (GPs) and incorporate GPs as components of larger graphical…