Yu Rong

Orcid: 0000-0001-7387-302X

Affiliations:
  • Alibaba DAMO Academy
  • Tecent AI Lab, Shenzhen, China (former)
  • Chinese University of Hong Kong, Hong Kong (former, PhD 2016)


According to our database1, Yu Rong authored at least 119 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2014
2016
2018
2020
2022
2024
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Legend:

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Online presence:

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Bibliography

2024
Structure-Aware DropEdge Toward Deep Graph Convolutional Networks.
IEEE Trans. Neural Networks Learn. Syst., November, 2024

Inductive Attributed Community Search: to Learn Communities across Graphs.
Proc. VLDB Endow., June, 2024

Recognizing Predictive Substructures With Subgraph Information Bottleneck.
IEEE Trans. Pattern Anal. Mach. Intell., March, 2024

Solving the non-submodular network collapse problems via Decision Transformer.
Neural Networks, 2024

Toward Robust Self-Training Paradigm for Molecular Prediction Tasks.
J. Comput. Biol., 2024

Graph Pre-Training Models Are Strong Anomaly Detectors.
CoRR, 2024

Adaptive Coordinators and Prompts on Heterogeneous Graphs for Cross-Domain Recommendations.
CoRR, 2024

Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning.
CoRR, 2024

MGCP: A Multi-Grained Correlation based Prediction Network for Multivariate Time Series.
CoRR, 2024

Atomas: Hierarchical Alignment on Molecule-Text for Unified Molecule Understanding and Generation.
CoRR, 2024

Functional Protein Design with Local Domain Alignment.
CoRR, 2024

All-in-One: Heterogeneous Interaction Modeling for Cold-Start Rating Prediction.
CoRR, 2024

A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications.
CoRR, 2024

Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Broad Physical Dynamics Learning.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Natural Language-Assisted Multi-modal Medication Recommendation.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Hierarchical Graph Latent Diffusion Model for Conditional Molecule Generation.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
Learned sketch for subgraph counting: a holistic approach.
VLDB J., September, 2023

Learning with Small Data: Subgraph Counting Queries.
Data Sci. Eng., September, 2023

scMHNN: a novel hypergraph neural network for integrative analysis of single-cell epigenomic, transcriptomic and proteomic data.
Briefings Bioinform., September, 2023

Adversarial Attack Framework on Graph Embedding Models With Limited Knowledge.
IEEE Trans. Knowl. Data Eng., May, 2023

Semi-Supervised Hierarchical Graph Classification.
IEEE Trans. Pattern Anal. Mach. Intell., May, 2023

Exploiting node-feature bipartite graph in graph convolutional networks.
Inf. Sci., May, 2023

Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions.
Trans. Mach. Learn. Res., 2023

Finding Critical Users in Social Communities via Graph Convolutions.
IEEE Trans. Knowl. Data Eng., 2023

Computing Graph Edit Distance via Neural Graph Matching.
Proc. VLDB Endow., 2023

Long-Range Neural Atom Learning for Molecular Graphs.
CoRR, 2023

Physics-Inspired Neural Graph ODE for Long-term Dynamical Simulation.
CoRR, 2023

Structure-Aware DropEdge Towards Deep Graph Convolutional Networks.
CoRR, 2023

Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Insights into Noisy Pseudo Labeling on Graph Data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Decision Support System for Chronic Diseases Based on Drug-Drug Interactions.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Geometric Graph Learning for Protein Mutation Effect Prediction.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Human Mobility Modeling during the COVID-19 Pandemic via Deep Graph Diffusion Infomax.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed.
Proc. VLDB Endow., 2022

Structure-aware conditional variational auto-encoder for constrained molecule optimization.
Pattern Recognit., 2022

Graph Convolutional Module for Temporal Action Localization in Videos.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Blood-brain barrier penetration prediction enhanced by uncertainty estimation.
J. Cheminformatics, 2022

Vertical Federated Linear Contextual Bandits.
CoRR, 2022

3D Equivariant Molecular Graph Pretraining.
CoRR, 2022

Similarity-aware Positive Instance Sampling for Graph Contrastive Pre-training.
CoRR, 2022

A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection.
CoRR, 2022

Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs.
CoRR, 2022

Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation.
CoRR, 2022

Equivariant Graph Hierarchy-Based Neural Networks.
CoRR, 2022

Transformer for Graphs: An Overview from Architecture Perspective.
CoRR, 2022

Geometrically Equivariant Graph Neural Networks: A Survey.
CoRR, 2022

Masked Transformer for Neighhourhood-aware Click-Through Rate Prediction.
CoRR, 2022

DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations.
CoRR, 2022

Cross-dependent graph neural networks for molecular property prediction.
Bioinform., 2022

Divide-and-Conquer: Post-User Interaction Network for Fake News Detection on Social Media.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Diversified Multiscale Graph Learning with Graph Self-Correction.
Proceedings of the Topological, 2022

Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Equivariant Graph Hierarchy-Based Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Local Augmentation for Graph Neural Networks.
Proceedings of the International Conference on Machine Learning, 2022

Frustratingly Easy Transferability Estimation.
Proceedings of the International Conference on Machine Learning, 2022

Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Equivariant Graph Mechanics Networks with Constraints.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Finding Critical Users in Social Communities via Graph Convolutions (Extended Abstract).
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Integrating Prior Knowledge with Graph Encoder for Gene Regulatory Inference from Single-cell RNA-Seq Data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

Robust self-training strategy for various molecular biology prediction tasks.
Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022

2021
Molecular graph enhanced transformer for retrosynthesis prediction.
Neurocomputing, 2021

Local Augmentation for Graph Neural Networks.
CoRR, 2021

PI-GNN: A Novel Perspective on Semi-Supervised Node Classification against Noisy Labels.
CoRR, 2021

Energy-Based Learning for Cooperative Games, with Applications to Feature/Data/Model Valuations.
CoRR, 2021

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks.
CoRR, 2021

QD-GCN: Query-Driven Graph Convolutional Networks for Attributed Community Search.
CoRR, 2021

Diversified Multiscale Graph Learning with Graph Self-Correction.
CoRR, 2021

Graph Ordering: Towards the Optimal by Learning.
Proceedings of the Web Information Systems Engineering - WISE 2021, 2021

A Learned Sketch for Subgraph Counting.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Not All Low-Pass Filters are Robust in Graph Convolutional Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards Feature-free TSP Solver Selection: A Deep Learning Approach.
Proceedings of the International Joint Conference on Neural Networks, 2021

On Self-Distilling Graph Neural Network.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning Diverse-Structured Networks for Adversarial Robustness.
Proceedings of the 38th International Conference on Machine Learning, 2021

Graph Information Bottleneck for Subgraph Recognition.
Proceedings of the 9th International Conference on Learning Representations, 2021

Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Towards Expectation-Maximization by SQL in RDBMS.
Proceedings of the Database Systems for Advanced Applications, 2021

Unsupervised Large-Scale Social Network Alignment via Cross Network Embedding.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Spectral Graph Attention Network with Fast Eigen-approximation.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Gradient-Norm Based Attentive Loss for Molecular Property Prediction.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

Hierarchical Graph Capsule Network.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Maximizing the Reduction Ability for Near-maximum Independent Set Computation.
Proc. VLDB Endow., 2020

Dirichlet Graph Variational Autoencoder.
CoRR, 2020

Tackling Over-Smoothing for General Graph Convolutional Networks.
CoRR, 2020

Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?
CoRR, 2020

GROVER: Self-supervised Message Passing Transformer on Large-scale Molecular Data.
CoRR, 2020

Leveraging TSP Solver Complementarity via Deep Learning.
CoRR, 2020

Dual Message Passing Neural Network for Molecular Property Prediction.
CoRR, 2020

Spectral Graph Attention Network.
CoRR, 2020

Graph Ordering: Towards the Optimal by Learning.
CoRR, 2020

Graph Representation Learning via Graphical Mutual Information Maximization.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Adversarial Attack on Community Detection by Hiding Individuals.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Deep Multimodal Fusion by Channel Exchanging.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Self-Supervised Graph Transformer on Large-Scale Molecular Data.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Dirichlet Graph Variational Autoencoder.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Deep Graph Learning: Foundations, Advances and Applications.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification.
Proceedings of the 8th International Conference on Learning Representations, 2020

A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
The General Black-box Attack Method for Graph Neural Networks.
CoRR, 2019

The Truly Deep Graph Convolutional Networks for Node Classification.
CoRR, 2019

Unsupervised Adversarial Graph Alignment with Graph Embedding.
CoRR, 2019

Adversarial Representation Learning on Large-Scale Bipartite Graphs.
CoRR, 2019

Semi-Supervised Graph Classification: A Hierarchical Graph Perspective.
Proceedings of the World Wide Web Conference, 2019

Graph Convolutional Networks for Temporal Action Localization.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Progressive Feature Alignment for Unsupervised Domain Adaptation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
On the Acceleration of L-BFGS with Second-Order Information and Stochastic Batches.
CoRR, 2018

Adaptive Sampling Towards Fast Graph Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

TATC: Predicting Alzheimer's Disease with Actigraphy Data.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Exploiting Ranking Consistency Principle in Representation Learning for Location Promotion.
Proceedings of the Database Systems for Advanced Applications, 2018

2017
Minimizing Dependence between Graphs.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016
A Model-Free Approach to Infer the Diffusion Network from Event Cascade.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015
Why It Happened: Identifying and Modeling the Reasons of the Happening of Social Events.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014
A Monte Carlo algorithm for cold start recommendation.
Proceedings of the 23rd International World Wide Web Conference, 2014


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