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07/20/2023
SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models
Recent advances in large language models (LLMs) have demonstrated notabl...
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01/10/2023
Neighborhood-Regularized Self-Training for Learning with Few Labels
Training deep neural networks (DNNs) with limited supervision has been a...
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12/20/2022
A Survey on Pretrained Language Models for Neural Code Intelligence
As the complexity of modern software continues to escalate, software eng...
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10/15/2022
Code Recommendation for Open Source Software Developers
Open Source Software (OSS) is forming the spines of technology infrastru...
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09/29/2022
Improving Molecular Pretraining with Complementary Featurizations
Molecular pretraining, which learns molecular representations over massi...
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06/30/2022
Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis
Human brains lie at the core of complex neurobiological systems, where t...
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06/09/2022
Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning
Brain networks characterize complex connectivities among brain regions a...
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03/17/2022
BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks
Mapping the connectome of the human brain using structural or functional...
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03/13/2022
A Survey on Deep Graph Generation: Methods and Applications
Graphs are ubiquitous in encoding relational information of real-world o...
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09/02/2021
An Empirical Study of Graph Contrastive Learning
Graph Contrastive Learning (GCL) establishes a new paradigm for learning...
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08/31/2021
Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning
Recently, heterogeneous Graph Neural Networks (GNNs) have become a de fa...
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08/16/2021
Deep Contrastive Learning for Multi-View Network Embedding
Multi-view network embedding aims at projecting nodes in the network to ...
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08/15/2021
Deep Active Learning for Text Classification with Diverse Interpretations
Recently, Deep Neural Networks (DNNs) have made remarkable progress for ...
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07/11/2021
BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis
Interpretable brain network models for disease prediction are of great v...
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07/07/2021
Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis
Multimodal brain networks characterize complex connectivities among diff...
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06/10/2021
Graph Symbiosis Learning
We introduce a framework for learning from multiple generated graph view...
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04/19/2021
Mining Latent Structures for Multimedia Recommendation
Multimedia content is of predominance in the modern Web era. Investigati...
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03/04/2021
Deep Graph Structure Learning for Robust Representations: A Survey
Graph Neural Networks (GNNs) are widely used for analyzing graph-structu...
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01/11/2021
Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction
Click-through rate (CTR) prediction, which aims to predict the probabili...
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10/30/2020
Deep Active Graph Representation Learning
Graph neural networks (GNNs) aim to learn graph representations that pre...
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10/27/2020
Graph Contrastive Learning with Adaptive Augmentation
Recently, contrastive learning (CL) has emerged as a successful method f...
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09/03/2020
CAGNN: Cluster-Aware Graph Neural Networks for Unsupervised Graph Representation Learning
Unsupervised graph representation learning aims to learn low-dimensional...
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06/07/2020
Deep Graph Contrastive Representation Learning
Graph representation learning nowadays becomes fundamental in analyzing ...
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05/06/2020
TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation
Session-based recommendation nowadays plays a vital role in many website...
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11/05/2019
GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction
Graph representation learning is of paramount importance for a variety o...
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02/13/2019
Semi-supervised Node Classification via Hierarchical Graph Convolutional Networks
Graph convolutional networks (GCNs) have been successfully applied in no...
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11/01/2018
Session-based Recommendation with Graph Neural Networks
The problem of session-based recommendation aims to predict users' actio...
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08/04/2018