Huiqi Deng

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 28

Top Topics

Input Variables

Subspace Learning

Top Venues

Mach. Intell. Res.

Pattern Recognit.

Publications

Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Mengnan Du
Explainability for Large Language Models: A Survey. ACM Trans. Intell. Syst. Technol. 15 (2) (2024)
Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang
Unifying Fourteen Post-Hoc Attribution Methods With Taylor Interactions. IEEE Trans. Pattern Anal. Mach. Intell. 46 (7) (2024)
Huilin Zhou, Hao Zhang, Huiqi Deng, Dongrui Liu, Wen Shen, Shih-Han Chan, Quanshi Zhang
Explaining Generalization Power of a DNN Using Interactive Concepts. AAAI (2024)
Zirui He, Huiqi Deng, Haiyan Zhao, Ninghao Liu, Mengnan Du
Mitigating Shortcuts in Language Models with Soft Label Encoding. LREC/COLING (2024)
Hongbin Pei, Yuheng Xiong, Pinghui Wang, Jing Tao, Jialun Liu, Huiqi Deng, Jie Ma, Xiaohong Guan
Memory Disagreement: A Pseudo-Labeling Measure from Training Dynamics for Semi-supervised Graph Learning. WWW (2024)
Hongbin Pei, Taile Chen, Chen A, Huiqi Deng, Jing Tao, Pinghui Wang, Xiaohong Guan
HAGO-Net: Hierarchical Geometric Massage Passing for Molecular Representation Learning. AAAI (2024)
Huilin Zhou, Jie Ren, Huiqi Deng, Xu Cheng, Jinpeng Zhang, Quanshi Zhang
Interpretability of Neural Networks Based on Game-theoretic Interactions. Mach. Intell. Res. 21 (4) (2024)
Dongrui Liu, Huiqi Deng, Xu Cheng, Qihan Ren, Kangrui Wang, Quanshi Zhang
Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities. NeurIPS (2023)
Huilin Zhou, Hao Zhang, Huiqi Deng, Dongrui Liu, Wen Shen, Shih-Han Chan, Quanshi Zhang
Concept-Level Explanation for the Generalization of a DNN. CoRR (2023)
Xinhao Zheng, Huiqi Deng, Quanshi Zhang
Towards Attributions of Input Variables in a Coalition. CoRR (2023)
Qihan Ren, Huiqi Deng, Yunuo Chen, Siyu Lou, Quanshi Zhang
Bayesian Neural Networks Tend to Ignore Complex and Sensitive Concepts. CoRR (2023)
Qihan Ren, Huiqi Deng, Yunuo Chen, Siyu Lou, Quanshi Zhang
Bayesian Neural Networks Avoid Encoding Complex and Perturbation-Sensitive Concepts. ICML (2023)
Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang
Understanding and Unifying Fourteen Attribution Methods with Taylor Interactions. CoRR (2023)
Jie Ren, Mingjie Li, Qirui Chen, Huiqi Deng, Quanshi Zhang
Defining and Quantifying the Emergence of Sparse Concepts in DNNs. CVPR (2023)
Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Mengnan Du
Explainability for Large Language Models: A Survey. CoRR (2023)
Zirui He, Huiqi Deng, Haiyan Zhao, Ninghao Liu, Mengnan Du
Mitigating Shortcuts in Language Models with Soft Label Encoding. CoRR (2023)
Huiqi Deng, Qihan Ren, Hao Zhang, Quanshi Zhang
Discovering and Explaining the Representation Bottleneck of DNNS. ICLR (2022)
Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu
A Unified Taylor Framework for Revisiting Attribution Methods. AAAI (2021)
Huiqi Deng, Qihan Ren, Xu Chen, Hao Zhang, Jie Ren, Quanshi Zhang
Discovering and Explaining the Representation Bottleneck of DNNs. CoRR (2021)
Huiqi Deng, Na Zou, Weifu Chen, Guocan Feng, Mengnan Du, Xia Hu
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution. KDD (2021)
Huiqi Deng, Na Zou, Weifu Chen, Guocan Feng, Mengnan Du, Xia Hu
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution. CoRR (2021)
Jie Ren, Mingjie Li, Qirui Chen, Huiqi Deng, Quanshi Zhang
Towards Axiomatic, Hierarchical, and Symbolic Explanation for Deep Models. CoRR (2021)
Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu
A General Taylor Framework for Unifying and Revisiting Attribution Methods. CoRR (2021)
Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu
A Unified Taylor Framework for Revisiting Attribution Methods. CoRR (2020)
Huiqi Deng, Weifu Chen, Qi Shen, Andy Jinhua Ma, Pong C. Yuen, Guocan Feng
Invariant subspace learning for time series data based on dynamic time warping distance. Pattern Recognit. 102 (2020)
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
UA-CRNN: Uncertainty-Aware Convolutional Recurrent Neural Network for Mortality Risk Prediction. CIKM (2019)
Qingxiong Tan, Andy Jinhua Ma, Huiqi Deng, Vincent Wai-Sun Wong, Yee-Kit Tse, Terry Cheuk-Fung Yip, Grace Lai-Hung Wong, Ching Ling Jessica Yuet, Francis Ka-Leung Chan, Pong C. Yuen
A Hybrid Residual Network and Long Short-Term Memory Method for Peptic Ulcer Bleeding Mortality Prediction. AMIA (2018)
Huiqi Deng, Weifu Chen, Andy Jinhua Ma, Qi Shen, Pong C. Yuen, Guocan Feng
Robust Shapelets Learning: Transform-Invariant Prototypes. PRCV (3) (2018)