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03/26/2023
Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases
Complex logical query answering (CLQA) is a recently emerged task of gra...
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10/13/2022
Inductive Logical Query Answering in Knowledge Graphs
Formulating and answering logical queries is a standard communication in...
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06/07/2022
Learning to Efficiently Propagate for Reasoning on Knowledge Graphs
Path-based methods are more appealing solutions than embedding methods f...
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05/16/2022
Neural-Symbolic Models for Logical Queries on Knowledge Graphs
Answering complex first-order logic (FOL) queries on knowledge graphs is...
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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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06/13/2021
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
Link prediction is a very fundamental task on graphs. Inspired by tradit...
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01/26/2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
Molecular graph generation is a fundamental problem for drug discovery a...
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11/13/2019
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
Pre-trained language representation models (PLMs) learn effective langua...
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10/20/2019
Self-Adaptive Network Pruning
Deep convolutional neural networks have been proved successful on a wide...
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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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11/16/2018
Saliency Supervision: An Intuitive and Effective Approach for Pain Intensity Regression
Getting pain intensity from face images is an important problem in auton...
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07/05/2017