Lirong He

According to our database, Lirong He authored at least 19 papers between 2017 and 2025.

Collaborative distances:

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

2025

CEGRL-TKGR: A Causal Enhanced Graph Representation Learning Framework for Temporal Knowledge Graph Reasoning.

Jinze Sun, Yongpan Sheng, Lirong He, Yongbin Qin, Ming Liu, Tao Jia

Proceedings of the 31st International Conference on Computational Linguistics, 2025

2024

Spectral Superresolution Using Transformer with Convolutional Spectral Self-Attention.

Xiaomei Liao, Lirong He, Jiayou Mao, Meng Xu

Remote. Sens., May, 2024

CEGRL-TKGR: A Causal Enhanced Graph Representation Learning Framework for Improving Temporal Knowledge Graph Extrapolation Reasoning.

Jinze Sun, Yongpan Sheng, Lirong He

CoRR, 2024

TKGR-GPRSCL: Enhance Temporal Knowledge Graph Reasoning with Graph Structure-Aware Path Representation and Supervised Contrastive Learning.

Lizhu Xiong, Yongpan Sheng, Lirong He

Proceedings of the Natural Language Processing and Chinese Computing, 2024

2023

Boosting adversarial robustness via self-paced adversarial training.

Lirong He, Qingzhong Ai, Xincheng Yang, Yazhou Ren, Qifan Wang, Zenglin Xu

Neural Networks, October, 2023

Stein Variational Gradient Descent with Multiple Kernels.

Qingzhong Ai, Shiyu Liu, Lirong He, Zenglin Xu

Cogn. Comput., March, 2023

Edge enhancement improves adversarial robustness in image classification.

Lirong He, Qingzhong Ai, Yuqing Lei, Lili Pan, Yazhou Ren, Zenglin Xu

Neurocomputing, 2023

TKGR-RHETNE: A New Temporal Knowledge Graph Reasoning Model via Jointly Modeling Relevant Historical Event and Temporal Neighborhood Event Context.

Jinze Sun, Yongpan Sheng, Ling Zhan, Lirong He

Proceedings of the Neural Information Processing - 30th International Conference, 2023

Generative Oversampling for Imbalanced Data via Majority-Guided VAE.

Qingzhong Ai, Pengyun Wang, Lirong He, Liangjian Wen, Lujia Pan, Zenglin Xu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2021

Gradient estimation of information measures in deep learning.

Liangjian Wen, Haoli Bai, Lirong He, Yiji Zhou, Mingyuan Zhou, Zenglin Xu

Knowl. Based Syst., 2021

ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE.

Qingzhong Ai, Lirong He, Liangjian Wen, Shiyu Liu, Zenglin Xu

CoRR, 2021

ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE.

Qingzhong Ai, Lirong He, Shiyu Liu, Zenglin Xu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Mutual Information Gradient Estimation for Representation Learning.

Liangjian Wen, Yiji Zhou, Lirong He, Mingyuan Zhou, Zenglin Xu

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Deep Minimax Probability Machine.

Lirong He, Ziyi Guo, Kaizhu Huang, Zenglin Xu

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

2018

NeuralCP: Bayesian Multiway Data Analysis with Neural Tensor Decomposition.

Bin Liu, Lirong He, Yingming Li, Shandian Zhe, Zenglin Xu

Cogn. Comput., 2018

Knowledge Base Completion by Variational Bayesian Neural Tensor Decomposition.

Lirong He, Bin Liu, Guangxi Li, Yongpan Sheng, Yafang Wang, Zenglin Xu

Cogn. Comput., 2018

Structured Inference for Recurrent Hidden Semi-markov Model.

Hao Liu, Lirong He, Haoli Bai, Bo Dai, Kun Bai, Zenglin Xu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

Stochastic Sequential Neural Networks with Structured Inference.

Hao Liu, Haoli Bai, Lirong He, Zenglin Xu

CoRR, 2017

Link prediction by exploiting network formation games in exchangeable graphs.

Liqiang Wang, Yafang Wang, Bin Liu, Lirong He, Shijun Liu, Gerard de Melo, Zenglin Xu

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017