Huiqi Deng

According to our database, Huiqi Deng authored at least 24 papers between 2018 and 2024.

Collaborative distances:

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

2024

Interpretability of Neural Networks Based on Game-theoretic Interactions.

Huilin Zhou, Jie Ren, Huiqi Deng, Xu Cheng, Jinpeng Zhang, Quanshi Zhang

Mach. Intell. Res., August, 2024

Explainability for Large Language Models: A Survey.

Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Mengnan Du

ACM Trans. Intell. Syst. Technol., April, 2024

Unifying Fourteen Post-Hoc Attribution Methods With Taylor Interactions.

Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang

IEEE Trans. Pattern Anal. Mach. Intell., 2024

Memory Disagreement: A Pseudo-Labeling Measure from Training Dynamics for Semi-supervised Graph Learning.

Hongbin Pei, Yuheng Xiong, Pinghui Wang, Jing Tao, Jialun Liu, Huiqi Deng, Jie Ma, Xiaohong Guan

Proceedings of the ACM on Web Conference 2024, 2024

Multi-Track Message Passing: Tackling Oversmoothing and Oversquashing in Graph Learning via Preventing Heterophily Mixing.

Hongbin Pei, Yu Li, Huiqi Deng, Jingxin Hai, Pinghui Wang, Jie Ma, Jing Tao, Yuheng Xiong, Xiaohong Guan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mitigating Shortcuts in Language Models with Soft Label Encoding.

Zirui He, Huiqi Deng, Haiyan Zhao, Ninghao Liu, Mengnan Du

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Explaining Generalization Power of a DNN Using Interactive Concepts.

Huilin Zhou, Hao Zhang, Huiqi Deng, Dongrui Liu, Wen Shen, Shih-Han Chan, Quanshi Zhang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

HAGO-Net: Hierarchical Geometric Massage Passing for Molecular Representation Learning.

Hongbin Pei, Taile Chen, Chen A, Huiqi Deng, Jing Tao, Pinghui Wang, Xiaohong Guan

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Towards Attributions of Input Variables in a Coalition.

Xinhao Zheng, Huiqi Deng, Quanshi Zhang

CoRR, 2023

Understanding and Unifying Fourteen Attribution Methods with Taylor Interactions.

Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang

CoRR, 2023

Bayesian Neural Networks Tend to Ignore Complex and Sensitive Concepts.

Qihan Ren, Huiqi Deng, Yunuo Chen, Siyu Lou, Quanshi Zhang

CoRR, 2023

Concept-Level Explanation for the Generalization of a DNN.

Huilin Zhou, Hao Zhang, Huiqi Deng, Dongrui Liu, Wen Shen, Shih-Han Chan, Quanshi Zhang

CoRR, 2023

Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities.

Dongrui Liu, Huiqi Deng, Xu Cheng, Qihan Ren, Kangrui Wang, Quanshi Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bayesian Neural Networks Avoid Encoding Complex and Perturbation-Sensitive Concepts.

Qihan Ren, Huiqi Deng, Yunuo Chen, Siyu Lou, Quanshi Zhang

Proceedings of the International Conference on Machine Learning, 2023

Defining and Quantifying the Emergence of Sparse Concepts in DNNs.

Jie Ren, Mingjie Li, Qirui Chen, Huiqi Deng, Quanshi Zhang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Discovering and Explaining the Representation Bottleneck of DNNS.

Huiqi Deng, Qihan Ren, Hao Zhang, Quanshi Zhang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Discovering and Explaining the Representation Bottleneck of DNNs.

Huiqi Deng, Qihan Ren, Xu Chen, Hao Zhang, Jie Ren, Quanshi Zhang

CoRR, 2021

Towards Axiomatic, Hierarchical, and Symbolic Explanation for Deep Models.

Jie Ren, Mingjie Li, Qirui Chen, Huiqi Deng, Quanshi Zhang

CoRR, 2021

Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution.

Huiqi Deng, Na Zou, Weifu Chen, Guocan Feng, Mengnan Du, Xia Hu

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

A Unified Taylor Framework for Revisiting Attribution Methods.

Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Invariant subspace learning for time series data based on dynamic time warping distance.

Huiqi Deng, Weifu Chen, Qi Shen, Andy Jinhua Ma, Pong C. Yuen, Guocan Feng

Pattern Recognit., 2020

2019

UA-CRNN: Uncertainty-Aware Convolutional Recurrent Neural Network for Mortality Risk Prediction.

Qingxiong Tan, Andy Jinhua Ma, Mang Ye, Baoyao Yang, Huiqi Deng, Vincent Wai-Sun Wong, Yee-Kit Tse, Terry Cheuk-Fung Yip, Grace Lai-Hung Wong, Jessica Yuet-Ling Ching, Francis Ka-Leung Chan, Pong C. Yuen

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018

Robust Shapelets Learning: Transform-Invariant Prototypes.

Huiqi Deng, Weifu Chen, Andy Jinhua Ma, Qi Shen, Pong C. Yuen, Guocan Feng

Proceedings of the Pattern Recognition and Computer Vision - First Chinese Conference, 2018

A Hybrid Residual Network and Long Short-Term Memory Method for Peptic Ulcer Bleeding Mortality Prediction.

Qingxiong Tan, Andy Jinhua Ma, Huiqi Deng, Vincent W. S. Wong, Yee-Kit Tse, Terry Cheuk-Fung Yip, Grace Lai-Hung Wong, Ching Ling Jessica Yuet, Francis Ka-Leung Chan, Pong C. Yuen

Proceedings of the AMIA 2018, 2018