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06/16/2021
Directed Graph Embeddings in Pseudo-Riemannian Manifolds
The inductive biases of graph representation learning algorithms are oft...
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06/15/2021
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
Learning meaningful representations of data that can address challenges ...
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12/01/2018
Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs
In this work, we provide a new formulation for Graph Convolutional Neura...
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03/08/2011
