30 citations · 119 across the 39 of their papers we have counts for
13 papers · 1 filter
Spatial Multivariate Trees for Big Data Bayesian Regression
Michele Peruzzi, David B. Dunson
High resolution geospatial data are challenging because standard geostatistical models based on Gaussian processes are known to not scale to large data sizes. While progress has be…
Bayesian nonparametric modelling of sequential discoveries
Alessandro Zito, Tommaso Rigon, Otso Ovaskainen +1
We aim at modelling the appearance of distinct tags in a sequence of labelled objects. Common examples of this type of data include words in a corpus or distinct species in a sampl…
Statistical Guarantees for Transformation Based Models with Applications to Implicit Variational Inference
Sean Plummer, Shuang Zhou, Anirban Bhattacharya +2
Transformation-based methods have been an attractive approach in non-parametric inference for problems such as unconditional and conditional density estimation due to their unique…
Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds
Lizhen Lin, Bayan Saparbayeva, Michael Minyi Zhang +1
We propose a general scheme for solving convex and non-convex optimization problems on manifolds. The central idea is that, by adding a multiple of the squared retraction distance…
Multi-scale graph principal component analysis for connectomics
Steven Winter, Zhengwu Zhang, David Dunson
In brain connectomics, the cortical surface is parcellated into different regions of interest (ROIs) prior to statistical analysis. The brain connectome for each individual can the…
Graph Based Gaussian Processes on Restricted Domains
David B Dunson, Hau-Tieng Wu, Nan Wu
In nonparametric regression, it is common for the inputs to fall in a restricted subset of Euclidean space. Typical kernel-based methods that do not take into account the intrinsic…