10 citations · 20 across the 6 of their papers we have counts for
3 papers
cs.LG2021★ 2 cited
Explicit Pairwise Factorized Graph Neural Network for Semi-Supervised Node Classification
Yu Wang, Yuesong Shen, Daniel Cremers
Node features and structural information of a graph are both crucial for semi-supervised node classification problems. A variety of graph neural network (GNN) based approaches have…
cs.LG2020★ 1 cited
A Chain Graph Interpretation of Real-World Neural Networks
Yuesong Shen, Daniel Cremers
The last decade has witnessed a boom of deep learning research and applications achieving state-of-the-art results in various domains. However, most advances have been established…
cs.LG2019★ 2 cited
Probabilistic Discriminative Learning with Layered Graphical Models
Yuesong Shen, Tao Wu, Csaba Domokos +1
Probabilistic graphical models are traditionally known for their successes in generative modeling. In this work, we advocate layered graphical models (LGMs) for probabilistic discr…