515 citations · 596 across the 9 of their papers we have counts for
13 papers
On the optimization and generalization of overparameterized implicit neural networks
Tianxiang Gao, Hongyang Gao
Implicit neural networks have become increasingly attractive in the machine learning community since they can achieve competitive performance but use much less computational resour…
Gradient Descent Optimizes Infinite-Depth ReLU Implicit Networks with Linear Widths
Tianxiang Gao, Hongyang Gao
Implicit deep learning has recently become popular in the machine learning community since these implicit models can achieve competitive performance with state-of-the-art deep netw…
Sent2Matrix: Folding Character Sequences in Serpentine Manifolds for Two-Dimensional Sentence
Hongyang Gao, Yi Liu, Xuan Zhang +1
We study text representation methods using deep models. Current methods, such as word-level embedding and character-level embedding schemes, treat texts as either a sequence of ato…
Topology-Aware Graph Pooling Networks
Hongyang Gao, Yi Liu, Shuiwang Ji
Pooling operations have shown to be effective on computer vision and natural language processing tasks. One challenge of performing pooling operations on graph data is the lack of…
Towards Deeper Graph Neural Networks
Meng Liu, Hongyang Gao, Shuiwang Ji
Graph neural networks have shown significant success in the field of graph representation learning. Graph convolutions perform neighborhood aggregation and represent one of the mos…
Kronecker Attention Networks
Hongyang Gao, Zhengyang Wang, Shuiwang Ji
Attention operators have been applied on both 1-D data like texts and higher-order data such as images and videos. Use of attention operators on high-order data requires flattening…