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An Empirical Evaluation of Rule Extraction from Recurrent Neural
  Networks
v1v2v3v4v5 (latest)

An Empirical Evaluation of Rule Extraction from Recurrent Neural Networks

29 September 2017
Qinglong Wang
Kaixuan Zhang
Alexander Ororbia
Masashi Sugiyama
Xue Liu
C. Lee Giles
ArXiv (abs)PDFHTML

Papers citing "An Empirical Evaluation of Rule Extraction from Recurrent Neural Networks"

18 / 18 papers shown
Title
Analyzing constrained LLM through PDFA-learning
Analyzing constrained LLM through PDFA-learning
Matías Carrasco
Franz Mayr
S. Yovine
Johny Kidd
Martín Iturbide
Juan da Silva
Alejo Garat
65
0
0
12 Jun 2024
On the Relationship Between RNN Hidden State Vectors and Semantic Ground
  Truth
On the Relationship Between RNN Hidden State Vectors and Semantic Ground Truth
Edi Muškardin
Martin Tappler
Ingo Pill
B. Aichernig
Thomas Pock
41
0
0
29 Jun 2023
State-Regularized Recurrent Neural Networks to Extract Automata and
  Explain Predictions
State-Regularized Recurrent Neural Networks to Extract Automata and Explain Predictions
Cheng Wang
Carolin (Haas) Lawrence
Mathias Niepert
69
3
0
10 Dec 2022
Extracting Finite Automata from RNNs Using State Merging
Extracting Finite Automata from RNNs Using State Merging
William Merrill
Nikolaos Tsilivis
85
15
0
28 Jan 2022
Minimum Description Length Recurrent Neural Networks
Minimum Description Length Recurrent Neural Networks
Nur Lan
Michal Geyer
Emmanuel Chemla
Roni Katzir
79
13
0
31 Oct 2021
Self-Supervised Learning to Prove Equivalence Between Straight-Line
  Programs via Rewrite Rules
Self-Supervised Learning to Prove Equivalence Between Straight-Line Programs via Rewrite Rules
Steve Kommrusch
Monperrus Martin
L. Pouchet
67
9
0
22 Sep 2021
Proving Equivalence Between Complex Expressions Using Graph-to-Sequence
  Neural Models
Proving Equivalence Between Complex Expressions Using Graph-to-Sequence Neural Models
Steven J Kommrusch
Théo Barollet
L. Pouchet
35
5
0
01 Jun 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A
  Systematic Survey of Surveys on Methods and Concepts
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts
Gesina Schwalbe
Bettina Finzel
XAI
153
198
0
15 May 2021
Uncertainty Estimation and Calibration with Finite-State Probabilistic
  RNNs
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
Cheng Wang
Carolin (Haas) Lawrence
Mathias Niepert
UQCV
58
10
0
24 Nov 2020
Equivalence of Dataflow Graphs via Rewrite Rules Using a
  Graph-to-Sequence Neural Model
Equivalence of Dataflow Graphs via Rewrite Rules Using a Graph-to-Sequence Neural Model
Steve Kommrusch
Théo Barollet
L. Pouchet
119
6
0
17 Feb 2020
Knowledge extraction from the learning of sequences in a long short term
  memory (LSTM) architecture
Knowledge extraction from the learning of sequences in a long short term memory (LSTM) architecture
Ikram Chraibi Kaadoud
N. Rougier
F. Alexandre
21
22
0
06 Dec 2019
Towards Interpreting Recurrent Neural Networks through Probabilistic
  Abstraction
Towards Interpreting Recurrent Neural Networks through Probabilistic Abstraction
Guoliang Dong
Jingyi Wang
Jun Sun
Yang Zhang
Xinyu Wang
Ting Dai
J. Dong
Xingen Wang
FaML
33
3
0
22 Sep 2019
Measurable Counterfactual Local Explanations for Any Classifier
Measurable Counterfactual Local Explanations for Any Classifier
Adam White
Artur Garcez
FAtt
73
98
0
08 Aug 2019
Learning Causal State Representations of Partially Observable
  Environments
Learning Causal State Representations of Partially Observable Environments
Amy Zhang
Zachary Chase Lipton
Luis Villaseñor-Pineda
Kamyar Azizzadenesheli
Anima Anandkumar
Laurent Itti
Joelle Pineau
Tommaso Furlanello
CML
115
51
0
25 Jun 2019
Neural-Symbolic Computing: An Effective Methodology for Principled
  Integration of Machine Learning and Reasoning
Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning
Artur Garcez
Marco Gori
Luís C. Lamb
Luciano Serafini
Michael Spranger
Son N. Tran
NAI
122
296
0
15 May 2019
State-Regularized Recurrent Neural Networks
State-Regularized Recurrent Neural Networks
Cheng Wang
Mathias Niepert
70
40
0
25 Jan 2019
Learning with Interpretable Structure from Gated RNN
Learning with Interpretable Structure from Gated RNN
Bo-Jian Hou
Zhi Zhou
AI4CE
75
70
0
25 Oct 2018
A Comparative Study of Rule Extraction for Recurrent Neural Networks
A Comparative Study of Rule Extraction for Recurrent Neural Networks
Qinglong Wang
Kaixuan Zhang
Alexander Ororbia
Masashi Sugiyama
Xue Liu
C. Lee Giles
80
11
0
16 Jan 2018
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