ICLR

Graph Neural Networks with Learnable Structural and Positional Representations
Graph neural networks (GNNs) have become the standard learning architectures for graphs. GNNs have been applied to numerous domains …
Towards Robustness Against Natural Language Word Substitutions
Robustness against word substitutions has a well-defined and widely acceptable form, i.e., using semantically similar words as …
Beyond Fully-Connected Layers with Quaternions:Parameterization of Hypercomplex Multiplications with 1/n Parameters
Recent works have demonstrated reasonable success of representation learning in hypercomplex space. Specifically, …