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20172021
most citedCompositional Fairness Constraints for Graph Embeddings

96 citations · 205 across the 5 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

cs.LG2020

TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion

Jiapeng Wu, Meng Cao, Jackie Chi Kit Cheung +1

Inferring missing facts in temporal knowledge graphs (TKGs) is a fundamental and challenging task. Previous works have approached this problem by augmenting methods for static know…

cs.LG2020

Structure Aware Negative Sampling in Knowledge Graphs

Kian Ahrabian, Aarash Feizi, Yasmin Salehi +2

Learning low-dimensional representations for entities and relations in knowledge graphs using contrastive estimation represents a scalable and effective method for inferring connec…

cs.LG2020

Directional Graph Networks

Dominique Beaini, Saro Passaro, Vincent Létourneau +3

The lack of anisotropic kernels in graph neural networks (GNNs) strongly limits their expressiveness, contributing to well-known issues such as over-smoothing. To overcome this lim…

cs.LG2020

Adversarial Example Games

Avishek Joey Bose, Gauthier Gidel, Hugo Berard +4

The existence of adversarial examples capable of fooling trained neural network classifiers calls for a much better understanding of possible attacks to guide the development of sa…

cs.CL2020

Learning an Unreferenced Metric for Online Dialogue Evaluation

Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang +3

Evaluating the quality of a dialogue interaction between two agents is a difficult task, especially in open-domain chit-chat style dialogue. There have been recent efforts to devel…

cs.LG2020

Evaluating Logical Generalization in Graph Neural Networks

Koustuv Sinha, Shagun Sodhani, Joelle Pineau +1

Recent research has highlighted the role of relational inductive biases in building learning agents that can generalize and reason in a compositional manner. However, while relatio…