Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint

18 December 2022

Jie Zhou

Papers citing "Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint"

48 / 48 papers shown

Title
Self-Explaining Hypergraph Neural Networks for Diagnosis Prediction Leisheng Yu Yanxiao Cai Minxing Zhang Xia Hu FAtt 333 0 0 15 Feb 2025
SWEA: Updating Factual Knowledge in Large Language Models via Subject Word Embedding Altering Xiaopeng Li Huijun Liu Shangwen Wang Bin Ji Bing Ji ... Jun Ma Jie Yu Xiaodong Liu Jing Wang Weimin Zhang KELM 87 4 0 31 Jan 2024
Enhance the Visual Representation via Discrete Adversarial Training Xiaofeng Mao YueFeng Chen Ranjie Duan Yao Zhu Gege Qi Shaokai Ye Xiaodan Li Rong Zhang Hui Xue 63 32 0 16 Sep 2022
GlanceNets: Interpretabile, Leak-proof Concept-based Models Emanuele Marconato Andrea Passerini Stefano Teso 133 64 0 31 May 2022
Orthogonal Stochastic Configuration Networks with Adaptive Construction Parameter for Data Analytics Wei Dai Chuanfeng Ning Shiyu Pei Song Zhu Xuesong Wang 74 2 0 26 May 2022
Self-Interpretable Model with TransformationEquivariant Interpretation Yipei Wang Xiaoqian Wang 51 23 0 09 Nov 2021
Interpretable Compositional Convolutional Neural Networks Wen Shen Zhihua Wei Shikun Huang Binbin Zhang Jiaqi Fan Ping Zhao Quanshi Zhang FAtt 19 34 0 09 Jul 2021
Entropy-based Logic Explanations of Neural Networks Pietro Barbiero Gabriele Ciravegna Francesco Giannini Pietro Lio Marco Gori S. Melacci FAtt XAI 32 78 0 12 Jun 2021
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows Ze Liu Yutong Lin Yue Cao Han Hu Yixuan Wei Zheng Zhang Stephen Lin B. Guo ViT 213 21,051 0 25 Mar 2021
Benchmarking and Survey of Explanation Methods for Black Box Models F. Bodria F. Giannotti Riccardo Guidotti Francesca Naretto D. Pedreschi S. Rinzivillo XAI 60 224 0 25 Feb 2021
Training data-efficient image transformers & distillation through attention Hugo Touvron Matthieu Cord Matthijs Douze Francisco Massa Alexandre Sablayrolles Hervé Jégou ViT 238 6,657 0 23 Dec 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 180 40,217 0 22 Oct 2020
Sharpness-Aware Minimization for Efficiently Improving Generalization Pierre Foret Ariel Kleiner H. Mobahi Behnam Neyshabur AAML 144 1,314 0 03 Oct 2020
Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters Haoyun Liang Zhihao Ouyang Yuyuan Zeng Hang Su Zihao He Shutao Xia Jun Zhu Bo Zhang 41 47 0 16 Jul 2020
Neural Additive Models: Interpretable Machine Learning with Neural Nets Rishabh Agarwal Levi Melnick Nicholas Frosst Xuezhou Zhang Ben Lengerich R. Caruana Geoffrey E. Hinton 49 412 0 29 Apr 2020
NBDT: Neural-Backed Decision Trees Alvin Wan Lisa Dunlap Daniel Ho Jihan Yin Scott Lee Henry Jin Suzanne Petryk Sarah Adel Bargal Joseph E. Gonzalez 30 99 0 01 Apr 2020
Concept Whitening for Interpretable Image Recognition Zhi Chen Yijie Bei Cynthia Rudin FAtt 53 317 0 05 Feb 2020
RandAugment: Practical automated data augmentation with a reduced search space E. D. Cubuk Barret Zoph Jonathon Shlens Quoc V. Le MQ 169 3,458 0 30 Sep 2019
XRAI: Better Attributions Through Regions A. Kapishnikov Tolga Bolukbasi Fernanda Viégas Michael Terry FAtt XAI 39 212 0 06 Jun 2019
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features Sangdoo Yun Dongyoon Han Seong Joon Oh Sanghyuk Chun Junsuk Choe Y. Yoo OOD 557 4,735 0 13 May 2019
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes Yang You Jing Li Sashank J. Reddi Jonathan Hseu Sanjiv Kumar Srinadh Bhojanapalli Xiaodan Song J. Demmel Kurt Keutzer Cho-Jui Hsieh ODL 131 991 0 01 Apr 2019
This Looks Like That: Deep Learning for Interpretable Image Recognition Chaofan Chen Oscar Li Chaofan Tao A. Barnett Jonathan Su Cynthia Rudin 154 1,172 0 27 Jun 2018
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 97 1,159 0 19 Jun 2018
Explaining Explanations: An Overview of Interpretability of Machine Learning Leilani H. Gilpin David Bau Ben Z. Yuan Ayesha Bajwa Michael A. Specter Lalana Kagal XAI 63 1,849 0 31 May 2018
Universality of Deep Convolutional Neural Networks Ding-Xuan Zhou HAI PINN 163 513 0 28 May 2018
Visual Interpretability for Deep Learning: a Survey Quanshi Zhang Song-Chun Zhu FaML HAI 73 812 0 02 Feb 2018
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks Aditya Chattopadhyay Anirban Sarkar Prantik Howlader V. Balasubramanian FAtt 63 2,274 0 30 Oct 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 217 9,687 0 25 Oct 2017
Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions Oscar Li Hao Liu Chaofan Chen Cynthia Rudin 101 586 0 13 Oct 2017
Interpretable Convolutional Neural Networks Quanshi Zhang Ying Nian Wu Song-Chun Zhu FAtt 35 774 0 02 Oct 2017
The Expressive Power of Neural Networks: A View from the Width Zhou Lu Hongming Pu Feicheng Wang Zhiqiang Hu Liwei Wang 58 886 0 08 Sep 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 261 2,248 0 24 Jun 2017
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 169 2,211 0 12 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 330 21,459 0 22 May 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 28 1,514 0 11 Apr 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 78 3,848 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 70 5,920 0 04 Mar 2017
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis L. Zintgraf Taco S. Cohen T. Adel Max Welling FAtt 93 707 0 15 Feb 2017
Stochastic Configuration Networks: Fundamentals and Algorithms Dianhui Wang Ming Li 42 492 0 10 Feb 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 179 19,796 0 07 Oct 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 392 16,765 0 16 Feb 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 111 9,266 0 14 Dec 2015
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.1K 192,638 0 10 Dec 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 527 149,474 0 22 Dec 2014
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 137 4,653 0 21 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 711 99,991 0 04 Sep 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 112 7,252 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 189 15,825 0 12 Nov 2013