4 papers
Stochastic Variational Inference with Tuneable Stochastic Annealing
John Paisley, Ghazal Fazelnia, Brian Barr
We exploit the observation that stochastic variational inference (SVI) is a form of annealing and present a modified SVI approach -- applicable to both large and small datasets --…
Gaussian Process Tilted Nonparametric Density Estimation using Fisher Divergence Score Matching
John Paisley, Wei Zhang, Brian Barr
We propose a nonparametric density estimator based on the Gaussian process (GP) and derive three novel closed form learning algorithms based on Fisher divergence (FD) score matchin…
An Explainable Gaussian Process Auto-encoder for Tabular Data
Wei Zhang, Brian Barr, John Paisley
Explainable machine learning has attracted much interest in the community where the stakes are high. Counterfactual explanations methods have become an important tool in explaining…
Tabular Diffusion Counterfactual Explanations
Wei Zhang, Brian Barr, John Paisley
Counterfactual explanations methods provide an important tool in the field of {interpretable machine learning}. Recent advances in this direction have focused on diffusion models t…