Bayesian Neural Networks Avoid Encoding Complex and
Perturbation-Sensitive Concepts

Bayesian Neural Networks Avoid Encoding Complex and Perturbation-Sensitive Concepts

25 February 2023

Papers citing "Bayesian Neural Networks Avoid Encoding Complex and Perturbation-Sensitive Concepts"

10 / 10 papers shown

Title
Towards the Three-Phase Dynamics of Generalization Power of a DNN Yuxuan He Junpeng Zhang Hongyuan Zhang Quanshi Zhang AI4CE 26 0 0 11 May 2025
Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey Yunkai Dang Kaichen Huang Jiahao Huo Yibo Yan S. Huang ... Kun Wang Yong Liu Jing Shao Hui Xiong Xuming Hu LRM 96 14 0 03 Dec 2024
Why pre-training is beneficial for downstream classification tasks? Xin Jiang Xu Cheng Zechao Li 32 0 0 11 Oct 2024
SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference Yuan Zhang Chun-Kai Fan Junpeng Ma Wenzhao Zheng Tao Huang ... Denis A. Gudovskiy Tomoyuki Okuno Yohei Nakata Kurt Keutzer Shanghang Zhang VLM 25 37 0 06 Oct 2024
Where We Have Arrived in Proving the Emergence of Sparse Symbolic Concepts in AI Models Qihan Ren Maximilian Brunner Wen Shen S. Mintchev 34 11 0 03 May 2023
Does a Neural Network Really Encode Symbolic Concepts? Mingjie Li Quanshi Zhang 8 30 0 25 Feb 2023
Discovering and Explaining the Representation Bottleneck of DNNs Huiqi Deng Qihan Ren Hao Zhang Quanshi Zhang 32 59 0 11 Nov 2021
Defining and Quantifying the Emergence of Sparse Concepts in DNNs J. Ren Mingjie Li Qirui Chen Huiqi Deng Quanshi Zhang 12 31 0 11 Nov 2021
A Unified Game-Theoretic Interpretation of Adversarial Robustness Jie Ren Die Zhang Yisen Wang Lu Chen Zhanpeng Zhou ... Xu Cheng Xin Eric Wang Meng Zhou Jie Shi Quanshi Zhang AAML 64 22 0 12 Mar 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 252 9,134 0 06 Jun 2015