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10/26/2022
Learning on Large-scale Text-attributed Graphs via Variational Inference
This paper studies learning on text-attributed graphs (TAGs), where each...
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05/21/2022
KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification
This paper studies semi-supervised graph classification, which is an imp...
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04/15/2022
Neural Structured Prediction for Inductive Node Classification
This paper studies node classification in the inductive setting, i.e., a...
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02/22/2022
Structured Multi-task Learning for Molecular Property Prediction
Multi-task learning for molecular property prediction is becoming increa...
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02/16/2022
TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery
Machine learning has huge potential to revolutionize the field of drug d...
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10/08/2020
RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
This paper studies learning logic rules for reasoning on knowledge graph...
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07/05/2020
Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs
This paper studies few-shot relation extraction, which aims at predictin...
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06/24/2020
Graph Policy Network for Transferable Active Learning on Graphs
Graph neural networks (GNNs) have been attracting increasing popularity ...
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12/02/2019
Continuous Graph Neural Networks
This paper builds the connection between graph neural networks and tradi...
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09/25/2019
GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning
We present GraphMix, a regularization technique for Graph Neural Network...
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08/31/2019
Collaborative Policy Learning for Open Knowledge Graph Reasoning
In recent years, there has been a surge of interests in interpretable gr...
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07/06/2019
Weakly-supervised Knowledge Graph Alignment with Adversarial Learning
This paper studies aligning knowledge graphs from different sources or l...
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06/20/2019
Probabilistic Logic Neural Networks for Reasoning
Knowledge graph reasoning, which aims at predicting the missing facts th...
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06/18/2019
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
This paper focuses on two fundamental tasks of graph analysis: community...
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05/15/2019
GMNN: Graph Markov Neural Networks
This paper studies semi-supervised object classification in relational d...
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03/02/2019
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
Learning continuous representations of nodes is attracting growing inter...
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02/20/2019
Learning Dual Retrieval Module for Semi-supervised Relation Extraction
Relation extraction is an important task in structuring content of text ...
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11/09/2017
Weakly-supervised Relation Extraction by Pattern-enhanced Embedding Learning
Extracting relations from text corpora is an important task in text mini...
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09/19/2017
An Attention-based Collaboration Framework for Multi-View Network Representation Learning
Learning distributed node representations in networks has been attractin...
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06/25/2017
Automatic Synonym Discovery with Knowledge Bases
Recognizing entity synonyms from text has become a crucial task in many ...
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11/29/2016
Identity-sensitive Word Embedding through Heterogeneous Networks
Most existing word embedding approaches do not distinguish the same word...
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10/27/2016
CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
Extracting entities and relations for types of interest from text is imp...
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02/17/2016
Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding
Current systems of fine-grained entity typing use distant supervision in...
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08/02/2015
