Caihua Shan

Senior Researcher

出版物

表示方法:

- VidGuard-R1: AI-Generated Video Detection and Explanation via Reasoning MLLMs and RL
  
  Kyoungjun Park, Yifan Yang, Juheon Yi, Shicheng Zheng, Yifei Shen, Dongqi Han, Caihua Shan, Muhammad Muaz, Lili Qiu
  
  ICLR 2026 | April 2026
  
  Publication Publication
- Chain-of-Model Learning for Language Model
  
  Kaitao Song, Xiaohua Wang, Xu Tan, Huiqiang Jiang, Chengruidong Zhang, Yongliang Shen, LU Cen, Li, Zifan Song, Caihua Shan, Yansen Wang, Kan Ren, Xiaoqing Zheng, Tao Qin, Yuqing Yang, Dongsheng Li, Lili Qiu
  
  NeurIPS 2025 | May 2025
  
  DOI
- Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning
  
  Zehui Li, Vallijah Subasri, Yifei Shen, Dongsheng Li, Yiren Zhao, Guy-Bart Stan, Caihua Shan
  
  NeurIPS 2025 | February 2025
  
  DOI Publication Publication
- When Do LLMs Help With Node Classification? A Comprehensive Analysis
  
  Xixi Wu, Yifei Shen, Fangzhou Ge, Caihua Shan, Yizhu Jiao, Xiangguo Sun, Hong Cheng
  
  ICML 2025 | February 2025
  
  Publication
- Can Graph Learning Improve Task Planning?
  
  Xixi Wu, Yifei Shen, Caihua Shan, Kaitao Song, Siwei Wang, Bohang Zhang, Jiarui Feng, Hong Cheng, Wei Chen, Yun Xiong, Dongsheng Li
  
  NeurIPS 2024 | December 2024
  
  DOI Publication Publication
- Personalized progression modelling and prediction in Parkinson’s disease with a novel multi-modal graph approach
  
  Jie Lian, Xufang Luo, Caihua Shan, Dongqi Han, Chencheng Zhang, V. Vardhanabhuti, Dongsheng Li, Lili Qiu
  
  NPJ Parkinson's Disease | December 2024, 巻10
  
  DOI Publication Publication
- Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs
  
  Kai Wang, Siqiang Luo, Caihua Shan, Yifei Shen
  
  NeurIPS 2025 | October 2024
  
  Publication
- Training-free Multi-objective Diffusion Model for 3D Molecule Generation
  
  Xu Han, Caihua Shan, Yifei Shen, Can Xu, Han Yang, Xiang Li, Dongsheng Li
  
  ICLR 2024 | April 2024
  
  Publication
- CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling
  
  Yansen Wang, Kan Ren, Xinyang Jiang, Caihua Shan, Xufang Luo, Dongqi Han, Kaitao Song, Yifei Shen, Dongsheng Li
  
  ICML 2023 | August 2023
  
  Publication
- Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking
  
  Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao
  
  WWW 23 | April 2023
  
  Author's Version
- Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling
  
  Yuchen Fang, Kan Ren, Caihua Shan, Yifei Shen, You Li, Weinan Zhang, Yong Yu, Dongsheng Li
  
  AAAI 2023 | February 2023
  
  Publication
- RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation
  
  Yao Zhang, Yun Xiong, Yiheng Sun, Caihua Shan, Tian Lu, Hui Song, Yangyong Zhu
  
  CIKM 2022 | October 2022
  
  Publication
- CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis
  
  Shifu Yan, Caihua Shan, Wenyi Yang, Bixiong Xu, Dongsheng Li, Lili Qiu, Jie Tong, Qi Zhang
  
  KDD 2022 | August 2022
  
  Publication
- CLARE: A Semi-supervised Community Detection Algorithm
  
  Xixi Wu, Yao Zhang, Yun Xiong, Yizhu Jiao, Caihua Shan, Yangyong Zhu, Philip S Yu
  
  KDD 2022 | August 2022
  
  Publication
- Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  
  Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
  
  ICML 2022 | July 2022
  
  Publication
- RendNet: Unified 2D/3D Recognizer With Latent Space Rendering
  
  Ruoxi Shi, Xinyang Jiang, Caihua Shan, Yansen Wang, Dongsheng Li
  
  CVPR 2022 | June 2022
  
  Publication
- Recognizing Vector Graphics without Rasterization
  
  Xinyang Jiang, Lu Liu, Caihua Shan, Yifei Shen, Xuanyi Dong, Dongsheng Li
  
  NeurIPS 2021 | December 2021
  
  Publication
- Reinforcement Learning Enhanced Explainer for Graph Neural Networks
  
  Caihua Shan, Yifei Shen, Yao Zhang, Xiang Li, Dongsheng Li
  
  NeurIPS 2021 | December 2021
  
  Publication
- How Powerful is Graph Convolution for Recommendation?
  
  Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, Khaled Ben Letaief, Dongsheng Li
  
  Conference on Information and Knowledge Management (Oral) | November 2021
  
  Project: Inductive bias in neural architectures
  
  Publication
- CoPE: Modeling Continuous Propagation and Evolution on Interaction Graph
  
  Yao Zhang, Yun Xiong, Dongsheng Li, Caihua Shan, Kan Ren, Yangyong Zhu
  
  2021 Conference on Information and Knowledge Management | October 2021
  
  DOI PDF Publication
- How Powerful is Graph Convolution for Recommendation
  
  Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, B. Khaled Letaief, Dongsheng Li
  
  2021 Conference on Information and Knowledge Management | October 2021
  
  DOI Publication Publication Publication Publication

- VidGuard-R1: AI-Generated Video Detection and Explanation via Reasoning MLLMs and RL
  
  Kyoungjun Park, Yifan Yang, Juheon Yi, Shicheng Zheng, Yifei Shen, Dongqi Han, Caihua Shan, Muhammad Muaz, Lili Qiu
  
  ICLR 2026 | April 2026
  
  Publication Publication
- Chain-of-Model Learning for Language Model
  
  Kaitao Song, Xiaohua Wang, Xu Tan, Huiqiang Jiang, Chengruidong Zhang, Yongliang Shen, LU Cen, Li, Zifan Song, Caihua Shan, Yansen Wang, Kan Ren, Xiaoqing Zheng, Tao Qin, Yuqing Yang, Dongsheng Li, Lili Qiu
  
  NeurIPS 2025 | May 2025
  
  DOI
- Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning
  
  Zehui Li, Vallijah Subasri, Yifei Shen, Dongsheng Li, Yiren Zhao, Guy-Bart Stan, Caihua Shan
  
  NeurIPS 2025 | February 2025
  
  DOI Publication Publication
- When Do LLMs Help With Node Classification? A Comprehensive Analysis
  
  Xixi Wu, Yifei Shen, Fangzhou Ge, Caihua Shan, Yizhu Jiao, Xiangguo Sun, Hong Cheng
  
  ICML 2025 | February 2025
  
  Publication
- Personalized progression modelling and prediction in Parkinson’s disease with a novel multi-modal graph approach
  
  Jie Lian, Xufang Luo, Caihua Shan, Dongqi Han, Chencheng Zhang, V. Vardhanabhuti, Dongsheng Li, Lili Qiu
  
  NPJ Parkinson's Disease | December 2024, 巻10
  
  DOI Publication Publication
- Can Graph Learning Improve Task Planning?
  
  Xixi Wu, Yifei Shen, Caihua Shan, Kaitao Song, Siwei Wang, Bohang Zhang, Jiarui Feng, Hong Cheng, Wei Chen, Yun Xiong, Dongsheng Li
  
  NeurIPS 2024 | December 2024
  
  DOI Publication Publication
- Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs
  
  Kai Wang, Siqiang Luo, Caihua Shan, Yifei Shen
  
  NeurIPS 2025 | October 2024
  
  Publication
- Training-free Multi-objective Diffusion Model for 3D Molecule Generation
  
  Xu Han, Caihua Shan, Yifei Shen, Can Xu, Han Yang, Xiang Li, Dongsheng Li
  
  ICLR 2024 | April 2024
  
  Publication
- CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling
  
  Yansen Wang, Kan Ren, Xinyang Jiang, Caihua Shan, Xufang Luo, Dongqi Han, Kaitao Song, Yifei Shen, Dongsheng Li
  
  ICML 2023 | August 2023
  
  Publication
- Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking
  
  Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao
  
  WWW 23 | April 2023
  
  Author's Version
- Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling
  
  Yuchen Fang, Kan Ren, Caihua Shan, Yifei Shen, You Li, Weinan Zhang, Yong Yu, Dongsheng Li
  
  AAAI 2023 | February 2023
  
  Publication
- RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation
  
  Yao Zhang, Yun Xiong, Yiheng Sun, Caihua Shan, Tian Lu, Hui Song, Yangyong Zhu
  
  CIKM 2022 | October 2022
  
  Publication
- CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis
  
  Shifu Yan, Caihua Shan, Wenyi Yang, Bixiong Xu, Dongsheng Li, Lili Qiu, Jie Tong, Qi Zhang
  
  KDD 2022 | August 2022
  
  Publication
- Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  
  Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
  
  ICML 2022 | July 2022
  
  Publication
- Reinforcement Learning Enhanced Explainer for Graph Neural Networks
  
  Caihua Shan, Yifei Shen, Yao Zhang, Xiang Li, Dongsheng Li
  
  NeurIPS 2021 | December 2021
  
  Publication
- Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning
  
  Zehui Li, Vallijah Subasri, Yifei Shen, Dongsheng Li, Yiren Zhao, Guy-Bart Stan, Caihua Shan
  
  NeurIPS 2025 | February 2025
  
  DOI Publication Publication
- Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking
  
  Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao
  
  WWW 23 | April 2023
  
  Author's Version
- CLARE: A Semi-supervised Community Detection Algorithm
  
  Xixi Wu, Yao Zhang, Yun Xiong, Yizhu Jiao, Caihua Shan, Yangyong Zhu, Philip S Yu
  
  KDD 2022 | August 2022
  
  Publication
- How Powerful is Graph Convolution for Recommendation
  
  Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, B. Khaled Letaief, Dongsheng Li
  
  2021 Conference on Information and Knowledge Management | October 2021
  
  DOI Publication Publication Publication Publication
- CoPE: Modeling Continuous Propagation and Evolution on Interaction Graph
  
  Yao Zhang, Yun Xiong, Dongsheng Li, Caihua Shan, Kan Ren, Yangyong Zhu
  
  2021 Conference on Information and Knowledge Management | October 2021
  
  DOI PDF Publication
- How Powerful is Graph Convolution for Recommendation?
  
  Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, Khaled Ben Letaief, Dongsheng Li
  
  Conference on Information and Knowledge Management (Oral) | November 2021
  
  Project: Inductive bias in neural architectures
  
  Publication
- How Powerful is Graph Convolution for Recommendation
  
  Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, B. Khaled Letaief, Dongsheng Li
  
  2021 Conference on Information and Knowledge Management | October 2021
  
  DOI Publication Publication Publication Publication
- CoPE: Modeling Continuous Propagation and Evolution on Interaction Graph
  
  Yao Zhang, Yun Xiong, Dongsheng Li, Caihua Shan, Kan Ren, Yangyong Zhu
  
  2021 Conference on Information and Knowledge Management | October 2021
  
  DOI PDF Publication
- RendNet: Unified 2D/3D Recognizer With Latent Space Rendering
  
  Ruoxi Shi, Xinyang Jiang, Caihua Shan, Yansen Wang, Dongsheng Li
  
  CVPR 2022 | June 2022
  
  Publication
- Recognizing Vector Graphics without Rasterization
  
  Xinyang Jiang, Lu Liu, Caihua Shan, Yifei Shen, Xuanyi Dong, Dongsheng Li
  
  NeurIPS 2021 | December 2021
  
  Publication

- VidGuard-R1: AI-Generated Video Detection and Explanation via Reasoning MLLMs and RL
  
  Kyoungjun Park, Yifan Yang, Juheon Yi, Shicheng Zheng, Yifei Shen, Dongqi Han, Caihua Shan, Muhammad Muaz, Lili Qiu
  
  ICLR 2026 | April 2026
  
  Publication Publication
- Chain-of-Model Learning for Language Model
  
  Kaitao Song, Xiaohua Wang, Xu Tan, Huiqiang Jiang, Chengruidong Zhang, Yongliang Shen, LU Cen, Li, Zifan Song, Caihua Shan, Yansen Wang, Kan Ren, Xiaoqing Zheng, Tao Qin, Yuqing Yang, Dongsheng Li, Lili Qiu
  
  NeurIPS 2025 | May 2025
  
  DOI
- Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning
  
  Zehui Li, Vallijah Subasri, Yifei Shen, Dongsheng Li, Yiren Zhao, Guy-Bart Stan, Caihua Shan
  
  NeurIPS 2025 | February 2025
  
  DOI Publication Publication
- When Do LLMs Help With Node Classification? A Comprehensive Analysis
  
  Xixi Wu, Yifei Shen, Fangzhou Ge, Caihua Shan, Yizhu Jiao, Xiangguo Sun, Hong Cheng
  
  ICML 2025 | February 2025
  
  Publication
- Can Graph Learning Improve Task Planning?
  
  Xixi Wu, Yifei Shen, Caihua Shan, Kaitao Song, Siwei Wang, Bohang Zhang, Jiarui Feng, Hong Cheng, Wei Chen, Yun Xiong, Dongsheng Li
  
  NeurIPS 2024 | December 2024
  
  DOI Publication Publication
- Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs
  
  Kai Wang, Siqiang Luo, Caihua Shan, Yifei Shen
  
  NeurIPS 2025 | October 2024
  
  Publication
- Training-free Multi-objective Diffusion Model for 3D Molecule Generation
  
  Xu Han, Caihua Shan, Yifei Shen, Can Xu, Han Yang, Xiang Li, Dongsheng Li
  
  ICLR 2024 | April 2024
  
  Publication
- CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling
  
  Yansen Wang, Kan Ren, Xinyang Jiang, Caihua Shan, Xufang Luo, Dongqi Han, Kaitao Song, Yifei Shen, Dongsheng Li
  
  ICML 2023 | August 2023
  
  Publication
- Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking
  
  Xiang Li, Tiandi Ye, Caihua Shan, Dongsheng Li, Ming Gao
  
  WWW 23 | April 2023
  
  Author's Version
- Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling
  
  Yuchen Fang, Kan Ren, Caihua Shan, Yifei Shen, You Li, Weinan Zhang, Yong Yu, Dongsheng Li
  
  AAAI 2023 | February 2023
  
  Publication
- RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation
  
  Yao Zhang, Yun Xiong, Yiheng Sun, Caihua Shan, Tian Lu, Hui Song, Yangyong Zhu
  
  CIKM 2022 | October 2022
  
  Publication
- CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis
  
  Shifu Yan, Caihua Shan, Wenyi Yang, Bixiong Xu, Dongsheng Li, Lili Qiu, Jie Tong, Qi Zhang
  
  KDD 2022 | August 2022
  
  Publication
- CLARE: A Semi-supervised Community Detection Algorithm
  
  Xixi Wu, Yao Zhang, Yun Xiong, Yizhu Jiao, Caihua Shan, Yangyong Zhu, Philip S Yu
  
  KDD 2022 | August 2022
  
  Publication
- Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  
  Xiang Li, Renyu Zhu, Yao Cheng, Caihua Shan, Siqiang Luo, Dongsheng Li, Weining Qian
  
  ICML 2022 | July 2022
  
  Publication
- RendNet: Unified 2D/3D Recognizer With Latent Space Rendering
  
  Ruoxi Shi, Xinyang Jiang, Caihua Shan, Yansen Wang, Dongsheng Li
  
  CVPR 2022 | June 2022
  
  Publication
- Reinforcement Learning Enhanced Explainer for Graph Neural Networks
  
  Caihua Shan, Yifei Shen, Yao Zhang, Xiang Li, Dongsheng Li
  
  NeurIPS 2021 | December 2021
  
  Publication
- Recognizing Vector Graphics without Rasterization
  
  Xinyang Jiang, Lu Liu, Caihua Shan, Yifei Shen, Xuanyi Dong, Dongsheng Li
  
  NeurIPS 2021 | December 2021
  
  Publication
- How Powerful is Graph Convolution for Recommendation?
  
  Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, Khaled Ben Letaief, Dongsheng Li
  
  Conference on Information and Knowledge Management (Oral) | November 2021
  
  Project: Inductive bias in neural architectures
  
  Publication
- How Powerful is Graph Convolution for Recommendation
  
  Yifei Shen, Yongji Wu, Yao Zhang, Caihua Shan, Jun Zhang, B. Khaled Letaief, Dongsheng Li
  
  2021 Conference on Information and Knowledge Management | October 2021
  
  DOI Publication Publication Publication Publication
- CoPE: Modeling Continuous Propagation and Evolution on Interaction Graph
  
  Yao Zhang, Yun Xiong, Dongsheng Li, Caihua Shan, Kan Ren, Yangyong Zhu
  
  2021 Conference on Information and Knowledge Management | October 2021
  
  DOI PDF Publication
- Personalized progression modelling and prediction in Parkinson’s disease with a novel multi-modal graph approach
  
  Jie Lian, Xufang Luo, Caihua Shan, Dongqi Han, Chencheng Zhang, V. Vardhanabhuti, Dongsheng Li, Lili Qiu
  
  NPJ Parkinson's Disease | December 2024, 巻10
  
  DOI Publication Publication

Caihua Shan

出版物

VidGuard-R1: AI-Generated Video Detection and Explanation via Reasoning MLLMs and RL

Chain-of-Model Learning for Language Model

Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning

When Do LLMs Help With Node Classification? A Comprehensive Analysis

Can Graph Learning Improve Task Planning?

Personalized progression modelling and prediction in Parkinson’s disease with a novel multi-modal graph approach

Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs

Training-free Multi-objective Diffusion Model for 3D Molecule Generation

CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling

Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking

Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling

RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation

CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis

CLARE: A Semi-supervised Community Detection Algorithm

Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

RendNet: Unified 2D/3D Recognizer With Latent Space Rendering

Recognizing Vector Graphics without Rasterization

Reinforcement Learning Enhanced Explainer for Graph Neural Networks

How Powerful is Graph Convolution for Recommendation?

CoPE: Modeling Continuous Propagation and Evolution on Interaction Graph

How Powerful is Graph Convolution for Recommendation

VidGuard-R1: AI-Generated Video Detection and Explanation via Reasoning MLLMs and RL

Chain-of-Model Learning for Language Model

Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning

When Do LLMs Help With Node Classification? A Comprehensive Analysis

Personalized progression modelling and prediction in Parkinson’s disease with a novel multi-modal graph approach

Can Graph Learning Improve Task Planning?

Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs

Training-free Multi-objective Diffusion Model for 3D Molecule Generation

CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling

Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking

Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling

RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation

CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis

Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

Reinforcement Learning Enhanced Explainer for Graph Neural Networks

Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning

Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking

CLARE: A Semi-supervised Community Detection Algorithm

How Powerful is Graph Convolution for Recommendation

CoPE: Modeling Continuous Propagation and Evolution on Interaction Graph

How Powerful is Graph Convolution for Recommendation?

How Powerful is Graph Convolution for Recommendation

CoPE: Modeling Continuous Propagation and Evolution on Interaction Graph

RendNet: Unified 2D/3D Recognizer With Latent Space Rendering

Recognizing Vector Graphics without Rasterization

VidGuard-R1: AI-Generated Video Detection and Explanation via Reasoning MLLMs and RL

Chain-of-Model Learning for Language Model

Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning

When Do LLMs Help With Node Classification? A Comprehensive Analysis

Can Graph Learning Improve Task Planning?

Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs

Training-free Multi-objective Diffusion Model for 3D Molecule Generation

CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling

Self-supervised Semi-implicit Graph Variational Auto-encoders with Masking

Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling

RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation

CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis

CLARE: A Semi-supervised Community Detection Algorithm

Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

RendNet: Unified 2D/3D Recognizer With Latent Space Rendering

Reinforcement Learning Enhanced Explainer for Graph Neural Networks

Recognizing Vector Graphics without Rasterization

How Powerful is Graph Convolution for Recommendation?

How Powerful is Graph Convolution for Recommendation

CoPE: Modeling Continuous Propagation and Evolution on Interaction Graph

Personalized progression modelling and prediction in Parkinson’s disease with a novel multi-modal graph approach