Search Results for author:
Found 3 papers, 2 papers with code
Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box
We show on a variety of real-world problems that DADVI reliably finds good solutions with default settings (unlike ADVI) and, together with LR covariances, is typically faster and more accurate than standard ADVI.
Scaling multi-species occupancy models to large citizen science datasets
We evaluate the predictions on a spatially separated test set of 59, 338 records, comparing two different inference methods -- Markov chain Monte Carlo (MCMC) and variational inference (VI) -- to occupancy models fitted to each species separately using maximum likelihood.
Gaussian Process Priors for Dynamic Paired Comparison Modelling
Dynamic paired comparison models, such as Elo and Glicko, are frequently used for sports prediction and ranking players or teams.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
