Minglong Lei

According to our database, Minglong Lei authored at least 32 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Latent diffusion transformer for point cloud generation.

Junzhong Ji, Runfeng Zhao, Minglong Lei

Vis. Comput., June, 2024

Exploring Brain Effective Connectivity Networks Through Spatiotemporal Graph Convolutional Models.

Aixiao Zou, Junzhong Ji, Minglong Lei, Jinduo Liu, Yongduan Song

IEEE Trans. Neural Networks Learn. Syst., June, 2024

Two-level adversarial attacks for graph neural networks.

Chengxi Song, Lingfeng Niu, Minglong Lei

Inf. Sci., January, 2024

Decomposed Latent Diffusion Model for 3D Point Cloud Generation.

Runfeng Zhao, Junzhong Ji, Minglong Lei

Proceedings of the Pattern Recognition and Computer Vision - 7th Chinese Conference, 2024

Spatio-Temporal Transformer Network with Physical Knowledge Distillation for Weather Forecasting.

Jing He, Junzhong Ji, Minglong Lei

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Graph Influence Network.

Yong Shi, Pei Quan, Yang Xiao, Minglong Lei, Lingfeng Niu

IEEE Trans. Cybern., October, 2023

Self-Supervised Spatiotemporal Graph Neural Networks With Self-Distillation for Traffic Prediction.

Junzhong Ji, Fan Yu, Minglong Lei

IEEE Trans. Intell. Transp. Syst., February, 2023

Supervised Contrastive Learning With Structure Inference for Graph Classification.

Junzhong Ji, Hao Jia, Yating Ren, Minglong Lei

IEEE Trans. Netw. Sci. Eng., 2023

A Unified Pre-training and Adaptation Framework for Combinatorial Optimization on Graphs.

Ruibin Zeng, Minglong Lei, Lingfeng Niu, Lan Cheng

CoRR, 2023

A Survey on Spatio-Temporal Graph Neural Networks for Traffic Forecasting.

Can Zhang, Minglong Lei

Proceedings of the IEEE International Conference on Data Mining, 2023

2022

DigGCN: Learning Compact Graph Convolutional Networks via Diffusion Aggregation.

Minglong Lei, Pei Quan, Rongrong Ma, Yong Shi, Lingfeng Niu

IEEE Trans. Cybern., 2022

Latent neighborhood-based heterogeneous graph representation.

Yang Xiao, Pei Quan, Minglong Lei, Lingfeng Niu

Neural Networks, 2022

Self-supervised knowledge distillation for complementary label learning.

Jiabin Liu, Biao Li, Minglong Lei, Yong Shi

Neural Networks, 2022

FC-HAT: Hypergraph attention network for functional brain network classification.

Junzhong Ji, Yating Ren, Minglong Lei

Inf. Sci., 2022

Relation constraint self-attention for image captioning.

Junzhong Ji, Mingzhan Wang, Xiaodan Zhang, Minglong Lei, Liangqiong Qu

Neurocomputing, 2022

Supervised Contrastive Learning with Structure Inference for Graph Classification.

Hao Jia, Junzhong Ji, Minglong Lei

CoRR, 2022

Optimal Transport Guided Node Classification in Cross Networks.

Lei Zheng, Pei Quan, Minglong Lei, Yang Xiao, Lingfeng Niu

Proceedings of the 9th International Conference on Information Technology and Quantitative Management, 2022

A Brief Survey for Fake News Detection via Deep Learning Models.

Jia Li, Minglong Lei

Proceedings of the 9th International Conference on Information Technology and Quantitative Management, 2022

2021

Document-level relation extraction via graph transformer networks and temporal convolutional networks.

Yong Shi, Yang Xiao, Pei Quan, Minglong Lei, Lingfeng Niu

Pattern Recognit. Lett., 2021

Distant Supervision Relation Extraction via adaptive dependency-path and additional knowledge graph supervision.

Yong Shi, Yang Xiao, Pei Quan, Minglong Lei, Lingfeng Niu

Neural Networks, 2021

Deep attributed graph clustering with self-separation regularization and parameter-free cluster estimation.

Junzhong Ji, Ye Liang, Minglong Lei

Neural Networks, 2021

Multi-task Self-distillation for Graph-based Semi-Supervised Learning.

Yating Ren, Junzhong Ji, Lingfeng Niu, Minglong Lei

CoRR, 2021

Latent Network Embedding via Adversarial Auto-encoders.

Minglong Lei, Yong Shi, Lingfeng Niu

CoRR, 2021

2020

Discrete Embedding for Latent Networks.

Hong Yang, Ling Chen, Minglong Lei, Lingfeng Niu, Chuan Zhou, Peng Zhang

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Diffusion network embedding.

Yong Shi, Minglong Lei, Hong Yang, Lingfeng Niu

Pattern Recognit., 2019

Learning Robust Auto-Encoders With Regularizer for Linearity and Sparsity.

Yong Shi, Minglong Lei, Rongrong Ma, Lingfeng Niu

IEEE Access, 2019

A Brief Review of Receptive Fields in Graph Convolutional Networks.

Pei Quan, Yong Shi, Minglong Lei, Jiaxu Leng, Tianlin Zhang, Lingfeng Niu

Proceedings of the 2019 IEEE/WIC/ACM International Conference on Web Intelligence, 2019

Review of bankruptcy prediction using machine learning and deep learning techniques.

Yi Qu, Pei Quan, Minglong Lei, Yong Shi

Proceedings of the 7th International Conference on Information Technology and Quantitative Management, 2019

Optimization Strategies in Quantized Neural Networks: A Review.

Yuhan Lin, Minglong Lei, Lingfeng Niu

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

2018

Diffusion Based Network Embedding.

Yong Shi, Minglong Lei, Peng Zhang, Lingfeng Niu

CoRR, 2018

The Applications of Stochastic Models in Network Embedding: A Survey.

Minglong Lei, Yong Shi, Lingfeng Niu

Proceedings of the 2018 IEEE/WIC/ACM International Conference on Web Intelligence, 2018

Deep Streaming Graph Representations.

Minglong Lei, Yong Shi, Peijia Li, Lingfeng Niu

Proceedings of the Computational Science - ICCS 2018, 2018