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1901.03838
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Enhancing Explainability of Neural Networks through Architecture Constraints
12 January 2019
Zebin Yang
Aijun Zhang
Agus Sudjianto
AAML
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Papers citing
"Enhancing Explainability of Neural Networks through Architecture Constraints"
14 / 14 papers shown
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Rethinking Log Odds: Linear Probability Modelling and Expert Advice in Interpretable Machine Learning
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Freddy Lecue
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Posterior Regularized Bayesian Neural Network Incorporating Soft and Hard Knowledge Constraints
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Yutian Pang
Yongming Liu
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16 Oct 2022
Monotonic Neural Additive Models: Pursuing Regulated Machine Learning Models for Credit Scoring
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FaML
65
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21 Sep 2022
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
Patrick Zschech
Sven Weinzierl
Nico Hambauer
Sandra Zilker
Mathias Kraus
143
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19 Apr 2022
Designing Inherently Interpretable Machine Learning Models
Agus Sudjianto
Aijun Zhang
FaML
53
31
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02 Nov 2021
Explainable Hierarchical Imitation Learning for Robotic Drink Pouring
Dandan Zhang
Yu Zheng
Qiang Li
Lei Wei
Dongsheng Zhang
Zhengyou Zhang
55
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0
16 May 2021
Bias, Fairness, and Accountability with AI and ML Algorithms
Neng-Zhi Zhou
Zach Zhang
V. Nair
Harsh Singhal
Jie Chen
Agus Sudjianto
FaML
121
9
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13 May 2021
Generalized Constraints as A New Mathematical Problem in Artificial Intelligence: A Review and Perspective
Bao-Gang Hu
Hanbing Qu
AI4CE
105
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12 Nov 2020
A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research
Cody Watson
Nathan Cooper
David Nader-Palacio
Kevin Moran
Denys Poshyvanyk
84
116
0
14 Sep 2020
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions
Zebin Yang
Aijun Zhang
Agus Sudjianto
FAtt
170
130
0
16 Mar 2020
Interpretation and Simplification of Deep Forest
Sangwon Kim
Mira Jeong
ByoungChul Ko
FAtt
89
8
0
14 Jan 2020
A Survey of Binary Code Similarity
I. Haq
Juan Caballero
50
138
0
25 Sep 2019
1