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2020-12
Sobolev Wasserstein GAN.
2020-10
2020-09
RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
2020-08
Robustesse structurelle des architectures d'apprentissage profond
2020-07
GRADE: Graph Dynamic Embedding.
Few-shot Relation Extraction via Bayesian Meta-learning on Task Graphs
Continuous Graph Neural Networks
A Graph to Graphs Framework for Retrosynthesis Prediction
Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs
2020-06
Graph Policy Network for Transferable Active Learning on Graphs
Graph Policy Network for Transferable Active Learning on Graphs
2020-05
Deep Geometric Knowledge Distillation with Graphs
ICASSP 2020
(2020-05-04)
hal.archives-ouvertes.frPDF[Also on arXiv preprint arXiv:1911.03080 (2019-11-08)]2020-04
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices.
2019-12
Probabilistic Logic Neural Networks for Reasoning
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
2019-11
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
GRLA 2019: The first International Workshop on Graph Representation Learning and its Applications
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
2019-09
Empowering Graph Representation Learning with Paired Training and Graph Co-Attention
Transfer Active Learning For Graph Neural Networks
GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning
Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures
2019-08
An end-to-end neighborhood-based interaction model for knowledge-enhanced recommendation
Proceedings of the 1st International Workshop on Deep Learning Practice for High-Dimensional Sparse Data
(2019-08-05)
ui.adsabs.harvard.edu[LATEST on arXiv preprint arXiv:1908.04032 (2019-08-12)]Multi-scale Information Diffusion Prediction with Reinforced Recurrent Networks.
2019-07
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization
DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases
DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases
Weakly-supervised Knowledge Graph Alignment with Adversarial Learning
2019-06
Explainable Knowledge Graph-based Recommendation via Deep Reinforcement Learning
Learning Powerful Policies by Using Consistent Dynamics Model.
Attending Over Triads for Learning Signed Network Embedding.
Structural Robustness for Deep Learning Architectures
Introducing Graph Smoothness Loss for Training Deep Learning Architectures
Structural Robustness for Deep Learning Architectures
2019-05
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Drug-Drug Adverse Effect Prediction with Graph Co-Attention
2019-03
Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction.
AMIA 2019
(2019-03-01)
ui.adsabs.harvard.eduPDF[LATEST on arXiv preprint arXiv:1903.08652 (2019-03-20)]2018-09
Learning powerful policies and better dynamics models by encouraging consistency
Data Poisoning Attack against Unsupervised Node Embedding Methods
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