63 citations · 243 across the 23 of their papers we have counts for
5 papers · 1 filter
HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding
Yishi Xu, Dongsheng Wang, Bo Chen +3
Embedded topic models are able to learn interpretable topics even with large and heavy-tailed vocabularies. However, they generally hold the Euclidean embedding space assumption, l…
Knowledge-Aware Bayesian Deep Topic Model
Dongsheng Wang, Yishi Xu, Miaoge Li +4
We propose a Bayesian generative model for incorporating prior domain knowledge into hierarchical topic modeling. Although embedded topic models (ETMs) and its variants have gained…
Ordinal Graph Gamma Belief Network for Social Recommender Systems
Dongsheng Wang, Chaojie Wang, Bo Chen +1
To build recommender systems that not only consider user-item interactions represented as ordinal variables, but also exploit the social network describing the relationships betwee…
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings
Dongsheng Wang, Dandan Guo, He Zhao +4
A topic model is often formulated as a generative model that explains how each word of a document is generated given a set of topics and document-specific topic proportions. It is…
A Variational Edge Partition Model for Supervised Graph Representation Learning
Yilin He, Chaojie Wang, Hao Zhang +2
Graph neural networks (GNNs), which propagate the node features through the edges and learn how to transform the aggregated features under label supervision, have achieved great su…