Qingyun Sun | DeepAI

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Philip S. Yu
299 publications
Hao Peng
135 publications
Jan Kautz
134 publications
Qian Li
80 publications
Jianxin Li
63 publications
Jeannette Bohg
63 publications
Kenji Kawaguchi
62 publications
Lifang He
60 publications
Pengtao Xie
59 publications
Xiang Zhou
53 publications
Jia Wu
49 publications

∙ 04/11/2023

Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification

Learning unbiased node representations for imbalanced samples in the gra...

0 Xingcheng Fu, et al. ∙

∙ 01/28/2023

Unbiased and Efficient Self-Supervised Incremental Contrastive Learning

Contrastive Learning (CL) has been proved to be a powerful self-supervis...

0 Cheng Ji, et al. ∙

∙ 12/30/2022

Self-organization Preserved Graph Structure Learning with Principle of Relevant Information

Most Graph Neural Networks follow the message-passing paradigm, assuming...

0 Qingyun Sun, et al. ∙

∙ 11/15/2022

Type Information Utilized Event Detection via Multi-Channel GNNs in Electrical Power Systems

Event detection in power systems aims to identify triggers and event typ...

0 Qian Li, et al. ∙

∙ 10/02/2022

Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation

Social networks are considered to be heterogeneous graph neural networks...

0 Yuecen Wei, et al. ∙

∙ 08/17/2022

Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing

Topology-imbalance is a graph-specific imbalance problem caused by the u...

8 Qingyun Sun, et al. ∙

∙ 08/09/2022

Automating DBSCAN via Deep Reinforcement Learning

DBSCAN is widely used in many scientific and engineering fields because ...

26 Ruitong Zhang, et al. ∙

∙ 03/03/2022

Curvature Graph Generative Adversarial Networks

Generative adversarial network (GAN) is widely used for generalized and ...

0 Jianxin Li, et al. ∙

∙ 12/16/2021

Graph Structure Learning with Variational Information Bottleneck

Graph Neural Networks (GNNs) have shown promising results on a broad spe...

10 Qingyun Sun, et al. ∙

∙ 10/15/2021

ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network

Graph Neural Networks (GNNs) have been widely studied in various graph d...

10 Xingcheng Fu, et al. ∙

∙ 06/13/2021

Convex Sparse Blind Deconvolution

In the blind deconvolution problem, we observe the convolution of an unk...

11 Qingyun Sun, et al. ∙

∙ 05/22/2021

A Robust and Generalized Framework for Adversarial Graph Embedding

Graph embedding is essential for graph mining tasks. With the prevalence...

5 Jianxin Li, et al. ∙

∙ 04/12/2021

A Recipe for Global Convergence Guarantee in Deep Neural Networks

Existing global convergence guarantees of (stochastic) gradient descent ...

0 Kenji Kawaguchi, et al. ∙

∙ 01/20/2021

SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism

Graph representation learning has attracted increasing research attentio...

0 Qingyun Sun, et al. ∙

∙ 09/18/2020

GRAC: Self-Guided and Self-Regularized Actor-Critic

Deep reinforcement learning (DRL) algorithms have successfully been demo...

6 Lin Shao, et al. ∙

∙ 08/30/2020

Pairwise Learning for Name Disambiguation in Large-Scale Heterogeneous Academic Networks

Name disambiguation aims to identify unique authors with the same name. ...

24 Qingyun Sun, et al. ∙

∙ 05/14/2020

How to Close Sim-Real Gap? Transfer with Segmentation!

One fundamental difficulty in robotic learning is the sim-real gap probl...

0 Mengyuan Yan, et al. ∙

∙ 03/07/2020

Stochastic Modified Equations for Continuous Limit of Stochastic ADMM

Stochastic version of alternating direction method of multiplier (ADMM) ...

0 Xiang Zhou, et al. ∙

∙ 06/10/2019

Degrees of Freedom Analysis of Unrolled Neural Networks

Unrolled neural networks emerged recently as an effective model for lear...

5 Morteza Mardani, et al. ∙

∙ 06/01/2018

Neural Proximal Gradient Descent for Compressive Imaging

Recovering high-resolution images from limited sensory data typically le...

0 Morteza Mardani, et al. ∙

∙ 06/02/2016

Convolutional Imputation of Matrix Networks

A matrix network is a family of matrices, where the relationship between...

0 Qingyun Sun, et al. ∙

∙ 03/10/2016

Bayesian Opponent Exploitation in Imperfect-Information Games

Two fundamental problems in computational game theory are computing a Na...

0 Sam Ganzfried, et al. ∙

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