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Exact and Consistent Interpretation for Piecewise Linear Neural
  Networks: A Closed Form Solution
v1v2 (latest)

Exact and Consistent Interpretation for Piecewise Linear Neural Networks: A Closed Form Solution

17 February 2018
Lingyang Chu
X. Hu
Juhua Hu
Lanjun Wang
Jian Pei
ArXiv (abs)PDFHTML

Papers citing "Exact and Consistent Interpretation for Piecewise Linear Neural Networks: A Closed Form Solution"

46 / 46 papers shown
Title
A Multimodal XAI Framework for Trustworthy CNNs and Bias Detection in Deep Representation Learning
A Multimodal XAI Framework for Trustworthy CNNs and Bias Detection in Deep Representation Learning
Noor Islam S. Mohammad
106
0
0
14 Oct 2025
ReLU Networks as Random Functions: Their Distribution in Probability Space
ReLU Networks as Random Functions: Their Distribution in Probability Space
Shreyas Chaudhari
J. M. F. Moura
258
0
0
28 Mar 2025
Neural Symbolic Logical Rule Learner for Interpretable Learning
Neural Symbolic Logical Rule Learner for Interpretable Learning
Bowen Wei
Ziwei Zhu
AI4CE
156
0
0
21 Aug 2024
Learning Interpretable Rules for Scalable Data Representation and
  Classification
Learning Interpretable Rules for Scalable Data Representation and ClassificationIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Zhuo Wang
Wei Zhang
Ning Liu
Jianyong Wang
164
13
0
22 Oct 2023
A max-affine spline approximation of neural networks using the Legendre
  transform of a convex-concave representation
A max-affine spline approximation of neural networks using the Legendre transform of a convex-concave representation
Adam Perrett
Danny Wood
Gavin Brown
125
0
0
16 Jul 2023
Deep Contract Design via Discontinuous Networks
Deep Contract Design via Discontinuous NetworksNeural Information Processing Systems (NeurIPS), 2023
Tonghan Wang
Paul Dutting
Dmitry Ivanov
Inbal Talgam-Cohen
David C. Parkes
179
17
0
05 Jul 2023
Deep ReLU Networks Have Surprisingly Simple Polytopes
Deep ReLU Networks Have Surprisingly Simple Polytopes
Fenglei Fan
Wei Huang
Xiang-yu Zhong
Lecheng Ruan
T. Zeng
Huan Xiong
Haiwei Yang
236
5
0
16 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey
When Deep Learning Meets Polyhedral Theory: A Survey
Joey Huchette
Gonzalo Muñoz
Thiago Serra
Calvin Tsay
AI4CE
598
43
0
29 Apr 2023
The Power of Typed Affine Decision Structures: A Case Study
The Power of Typed Affine Decision Structures: A Case StudyInternational Journal on Software Tools for Technology Transfer (STTT) (STTT), 2023
Gerrit Nolte
Maximilian Schlüter
Alnis Murtovi
Bernhard Steffen
AAML
133
2
0
28 Apr 2023
Generating Post-hoc Explanations for Skip-gram-based Node Embeddings by
  Identifying Important Nodes with Bridgeness
Generating Post-hoc Explanations for Skip-gram-based Node Embeddings by Identifying Important Nodes with BridgenessNeural Networks (Neural Netw.), 2023
Hogun Park
Jennifer Neville
259
8
0
24 Apr 2023
Model Doctor for Diagnosing and Treating Segmentation Error
Model Doctor for Diagnosing and Treating Segmentation ErrorInternational Conference on Information Photonics (ICIP), 2023
Zhijie Jia
Lin Chen
Kaiwen Hu
Lechao Cheng
Zunlei Feng
Min-Gyoo Song
174
0
0
17 Feb 2023
Towards Rigorous Understanding of Neural Networks via
  Semantics-preserving Transformations
Towards Rigorous Understanding of Neural Networks via Semantics-preserving TransformationsInternational Journal on Software Tools for Technology Transfer (STTT) (STTT), 2023
Maximilian Schlüter
Gerrit Nolte
Alnis Murtovi
Bernhard Steffen
237
6
0
19 Jan 2023
Non-Linear Coordination Graphs
Non-Linear Coordination GraphsNeural Information Processing Systems (NeurIPS), 2022
Yipeng Kang
Tonghan Wang
Xiao-Ren Wu
Qianlan Yang
Chongjie Zhang
157
10
0
26 Oct 2022
A Survey of Neural Trees
A Survey of Neural Trees
Haoling Li
Mingli Song
Mengqi Xue
Haofei Zhang
Jingwen Ye
Lechao Cheng
Weilong Dai
AI4CE
284
6
0
07 Sep 2022
On the Bias-Variance Characteristics of LIME and SHAP in High Sparsity
  Movie Recommendation Explanation Tasks
On the Bias-Variance Characteristics of LIME and SHAP in High Sparsity Movie Recommendation Explanation Tasks
Claudia V. Roberts
Ehtsham Elahi
Ashok Chandrashekar
FAtt
160
5
0
09 Jun 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
Trustworthy Graph Neural Networks: Aspects, Methods and TrendsProceedings of the IEEE (Proc. IEEE), 2022
He Zhang
Bang Wu
Lizhen Qu
Shirui Pan
Hanghang Tong
Jian Pei
344
148
0
16 May 2022
A Rigorous Study of Integrated Gradients Method and Extensions to
  Internal Neuron Attributions
A Rigorous Study of Integrated Gradients Method and Extensions to Internal Neuron AttributionsInternational Conference on Machine Learning (ICML), 2022
Daniel Lundstrom
Tianjian Huang
Meisam Razaviyayn
FAtt
239
79
0
24 Feb 2022
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic
  Review on Evaluating Explainable AI
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AIACM Computing Surveys (ACM CSUR), 2022
Meike Nauta
Jan Trienes
Shreyasi Pathak
Elisa Nguyen
Michelle Peters
Yasmin Schmitt
Jorg Schlotterer
M. V. Keulen
C. Seifert
ELMXAI
555
550
0
20 Jan 2022
Traversing the Local Polytopes of ReLU Neural Networks: A Unified
  Approach for Network Verification
Traversing the Local Polytopes of ReLU Neural Networks: A Unified Approach for Network Verification
Shaojie Xu
J. Vaughan
Jie Chen
Aijun Zhang
Agus Sudjianto
AAML
135
15
0
17 Nov 2021
Training Neural Networks for Solving 1-D Optimal Piecewise Linear
  Approximation
Training Neural Networks for Solving 1-D Optimal Piecewise Linear Approximation
Hangcheng Dong
Jing-Xiao Liao
Yan Wang
Yixin Chen
Bingguo Liu
Dong Ye
Guodong Liu
660
0
0
14 Oct 2021
Scalable Rule-Based Representation Learning for Interpretable
  Classification
Scalable Rule-Based Representation Learning for Interpretable Classification
Zhuo Wang
Wei Zhang
Ning Liu
Jianyong Wang
139
74
0
30 Sep 2021
Deep Active Learning for Text Classification with Diverse
  Interpretations
Deep Active Learning for Text Classification with Diverse Interpretations
Qiang Liu
Yanqiao Zhu
Zhaocheng Liu
Yufeng Zhang
Shu Wu
AI4CE
140
16
0
15 Aug 2021
Finding Representative Interpretations on Convolutional Neural Networks
Finding Representative Interpretations on Convolutional Neural NetworksIEEE International Conference on Computer Vision (ICCV), 2021
P. C. Lam
Lingyang Chu
Maxim Torgonskiy
Jian Pei
Yong Zhang
Lanjun Wang
FAttSSLHAI
159
7
0
13 Aug 2021
Robust Counterfactual Explanations on Graph Neural Networks
Robust Counterfactual Explanations on Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2021
Mohit Bajaj
Lingyang Chu
Zihui Xue
Jian Pei
Lanjun Wang
P. C. Lam
Yong Zhang
OOD
378
113
0
08 Jul 2021
Learning and Meshing from Deep Implicit Surface Networks Using an
  Efficient Implementation of Analytic Marching
Learning and Meshing from Deep Implicit Surface Networks Using an Efficient Implementation of Analytic MarchingIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Jiabao Lei
Kui Jia
Yi-An Ma
141
12
0
18 Jun 2021
How to Explain Neural Networks: an Approximation Perspective
How to Explain Neural Networks: an Approximation Perspective
Hangcheng Dong
Bingguo Liu
Fengdong Chen
Dong Ye
Guodong Liu
FAtt
143
1
0
17 May 2021
DNN2LR: Automatic Feature Crossing for Credit Scoring
DNN2LR: Automatic Feature Crossing for Credit Scoring
Qiang Liu
Zhaocheng Liu
Haoli Zhang
Yuntian Chen
Jun Zhu
121
0
0
24 Feb 2021
The Self-Simplifying Machine: Exploiting the Structure of Piecewise
  Linear Neural Networks to Create Interpretable Models
The Self-Simplifying Machine: Exploiting the Structure of Piecewise Linear Neural Networks to Create Interpretable Models
William Knauth
94
1
0
02 Dec 2020
Unwrapping The Black Box of Deep ReLU Networks: Interpretability,
  Diagnostics, and Simplification
Unwrapping The Black Box of Deep ReLU Networks: Interpretability, Diagnostics, and Simplification
Agus Sudjianto
William Knauth
Rahul Singh
Zebin Yang
Aijun Zhang
FAtt
208
50
0
08 Nov 2020
DNN2LR: Interpretation-inspired Feature Crossing for Real-world Tabular
  Data
DNN2LR: Interpretation-inspired Feature Crossing for Real-world Tabular Data
Zhaocheng Liu
Qiang Liu
Haoli Zhang
Yuntian Chen
170
13
0
22 Aug 2020
Deep Active Learning by Model Interpretability
Deep Active Learning by Model Interpretability
Qiang Liu
Zhaocheng Liu
Xiaofang Zhu
Yeliang Xiu
206
4
0
23 Jul 2020
Explainable Artificial Intelligence: a Systematic Review
Explainable Artificial Intelligence: a Systematic Review
Giulia Vilone
Luca Longo
XAI
559
300
0
29 May 2020
Analytic Marching: An Analytic Meshing Solution from Deep Implicit
  Surface Networks
Analytic Marching: An Analytic Meshing Solution from Deep Implicit Surface NetworksInternational Conference on Machine Learning (ICML), 2020
Jiabao Lei
Kui Jia
116
24
0
16 Feb 2020
Quasi-Equivalence of Width and Depth of Neural Networks
Quasi-Equivalence of Width and Depth of Neural Networks
Fenglei Fan
Rongjie Lai
Ge Wang
482
12
0
06 Feb 2020
On Interpretability of Artificial Neural Networks: A Survey
On Interpretability of Artificial Neural Networks: A SurveyIEEE Transactions on Radiation and Plasma Medical Sciences (TRPMS), 2020
Fenglei Fan
Jinjun Xiong
Mengzhou Li
Ge Wang
AAMLAI4CE
389
371
0
08 Jan 2020
Transparent Classification with Multilayer Logical Perceptrons and
  Random Binarization
Transparent Classification with Multilayer Logical Perceptrons and Random BinarizationAAAI Conference on Artificial Intelligence (AAAI), 2019
Zhuo Wang
Wei Zhang
Ning Liu
Jianyong Wang
128
37
0
10 Dec 2019
GRACE: Generating Concise and Informative Contrastive Sample to Explain
  Neural Network Model's Prediction
GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model's Prediction
Thai V. Le
Suhang Wang
Dongwon Lee
155
1
0
05 Nov 2019
Exact and Consistent Interpretation of Piecewise Linear Models Hidden
  behind APIs: A Closed Form Solution
Exact and Consistent Interpretation of Piecewise Linear Models Hidden behind APIs: A Closed Form SolutionIEEE International Conference on Data Engineering (ICDE), 2019
Zicun Cong
Lingyang Chu
Lanjun Wang
X. Hu
Jian Pei
773
5
0
17 Jun 2019
Exploring Interpretable LSTM Neural Networks over Multi-Variable Data
Exploring Interpretable LSTM Neural Networks over Multi-Variable DataInternational Conference on Machine Learning (ICML), 2019
Tian Guo
Tao Lin
Nino Antulov-Fantulin
AI4TS
185
173
0
28 May 2019
On Attribution of Recurrent Neural Network Predictions via Additive
  Decomposition
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition
Mengnan Du
Ninghao Liu
Fan Yang
Shuiwang Ji
Helen Zhou
FAtt
125
52
0
27 Mar 2019
Multi-Granularity Reasoning for Social Relation Recognition from Images
Multi-Granularity Reasoning for Social Relation Recognition from Images
Meng Zhang
Xinchen Liu
Wu Liu
Anfu Zhou
Huadong Ma
Tao Mei
159
50
0
10 Jan 2019
Soft Autoencoder and Its Wavelet Adaptation Interpretation
Soft Autoencoder and Its Wavelet Adaptation Interpretation
Fenglei Fan
Mengzhou Li
Yueyang Teng
Ge Wang
195
4
0
31 Dec 2018
A Survey of Safety and Trustworthiness of Deep Neural Networks:
  Verification, Testing, Adversarial Attack and Defence, and Interpretability
A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability
Xiaowei Huang
Daniel Kroening
Wenjie Ruan
Marta Kwiatkowska
Youcheng Sun
Emese Thamo
Min Wu
Xinping Yi
AAML
436
52
0
18 Dec 2018
A Multidisciplinary Survey and Framework for Design and Evaluation of
  Explainable AI Systems
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems
Sina Mohseni
Niloofar Zarei
Eric D. Ragan
388
103
0
28 Nov 2018
Techniques for Interpretable Machine Learning
Techniques for Interpretable Machine Learning
Mengnan Du
Ninghao Liu
Helen Zhou
FaML
419
1,189
0
31 Jul 2018
Fuzzy Logic Interpretation of Quadratic Networks
Fuzzy Logic Interpretation of Quadratic Networks
Fenglei Fan
Ge Wang
177
7
0
04 Jul 2018
1