21 citations · 60 across the 20 of their papers we have counts for
6 papers · 1 filter
Scalable Deep Generative Relational Models with High-Order Node Dependence
Xuhui Fan, Bin Li, Scott Anthony Sisson +2
We propose a probabilistic framework for modelling and exploring the latent structure of relational data. Given feature information for the nodes in a network, the scalable deep ge…
Scalable Inference for Nonparametric Hawkes Process Using Pólya-Gamma Augmentation
Feng Zhou, Zhidong Li, Xuhui Fan +3
In this paper, we consider the sigmoid Gaussian Hawkes process model: the baseline intensity and triggering kernel of Hawkes process are both modeled as the sigmoid transformation…
Fast Multi-resolution Segmentation for Nonstationary Hawkes Process Using Cumulants
Feng Zhou, Zhidong Li, Xuhui Fan +3
The stationarity is assumed in vanilla Hawkes process, which reduces the model complexity but introduces a strong assumption. In this paper, we propose a fast multi-resolution segm…
Binary Space Partitioning Forests
Xuhui Fan, Bin Li, Scott Anthony Sisson
The Binary Space Partitioning~(BSP)-Tree process is proposed to produce flexible 2-D partition structures which are originally used as a Bayesian nonparametric prior for relational…
The Binary Space Partitioning-Tree Process
Xuhui Fan, Bin Li, Scott Anthony Sisson
The Mondrian process represents an elegant and powerful approach for space partition modelling. However, as it restricts the partitions to be axis-aligned, its modelling flexibilit…
Rectangular Bounding Process
Xuhui Fan, Bin Li, Scott Anthony Sisson
Stochastic partition models divide a multi-dimensional space into a number of rectangular regions, such that the data within each region exhibit certain types of homogeneity. Due t…