This report gives a summary of two problems about graph convolutional
ne...
We present a new model for generating molecular data by combining discre...
Homophily principle, i.e. nodes with the same labels are more likely to ...
The core operation of current Graph Neural Networks (GNNs) is the aggreg...
Graph Neural Networks (GNNs) extend basic Neural Networks (NNs) by
addit...
Graph Neural Networks (GNNs) extend basic Neural Networks (NNs) by using...
Graph Neural Networks (GNNs) extend basic Neural Networks (NNs) by using...
We present an end-to-end, model-based deep reinforcement learning agent ...
The core operation of Graph Neural Networks (GNNs) is the aggregation en...
The performance limit of Graph Convolutional Networks (GCNs) and the fac...
In tabular case, when the reward and environment dynamics are known, pol...
Recently, neural network based approaches have achieved significant
impr...