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Automatic Rule Extraction from Long Short Term Memory Networks
v1v2 (latest)

Automatic Rule Extraction from Long Short Term Memory Networks

International Conference on Learning Representations (ICLR), 2016
8 February 2017
W. James Murdoch
Arthur Szlam
ArXiv (abs)PDFHTML

Papers citing "Automatic Rule Extraction from Long Short Term Memory Networks"

45 / 45 papers shown
Explainable Bayesian Optimization
Explainable Bayesian Optimization
Tanmay Chakraborty
Christin Seifert
Christin Seifert
439
9
0
24 Jan 2024
DEGREE: Decomposition Based Explanation For Graph Neural Networks
DEGREE: Decomposition Based Explanation For Graph Neural NetworksInternational Conference on Learning Representations (ICLR), 2023
Qizhang Feng
Ninghao Liu
Fan Yang
Ruixiang Tang
Mengnan Du
Helen Zhou
304
32
0
22 May 2023
Explainability of Text Processing and Retrieval Methods: A Survey
Explainability of Text Processing and Retrieval Methods: A Survey
Sourav Saha
Debapriyo Majumdar
Mandar Mitra
366
5
0
14 Dec 2022
State-Regularized Recurrent Neural Networks to Extract Automata and
  Explain Predictions
State-Regularized Recurrent Neural Networks to Extract Automata and Explain PredictionsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Cheng Wang
Carolin (Haas) Lawrence
Mathias Niepert
260
3
0
10 Dec 2022
Implicit N-grams Induced by Recurrence
Implicit N-grams Induced by RecurrenceNorth American Chapter of the Association for Computational Linguistics (NAACL), 2022
Xiaobing Sun
Wei Lu
287
5
0
05 May 2022
Interpreting and improving deep-learning models with reality checks
Interpreting and improving deep-learning models with reality checks
Chandan Singh
Wooseok Ha
Bin Yu
FAtt
283
4
0
16 Aug 2021
Pairing Conceptual Modeling with Machine Learning
Pairing Conceptual Modeling with Machine LearningData & Knowledge Engineering (DKE), 2021
W. Maass
V. Storey
HAI
226
44
0
27 Jun 2021
Explaining the Deep Natural Language Processing by Mining Textual
  Interpretable Features
Explaining the Deep Natural Language Processing by Mining Textual Interpretable Features
F. Ventura
Salvatore Greco
D. Apiletti
Tania Cerquitelli
139
2
0
12 Jun 2021
Explainability-aided Domain Generalization for Image Classification
Explainability-aided Domain Generalization for Image Classification
Robin M. Schmidt
FAttOOD
268
2
0
05 Apr 2021
TimeSHAP: Explaining Recurrent Models through Sequence Perturbations
TimeSHAP: Explaining Recurrent Models through Sequence PerturbationsKnowledge Discovery and Data Mining (KDD), 2020
João Bento
Pedro Saleiro
André F. Cruz
Mário A. T. Figueiredo
P. Bizarro
FAttAI4TS
523
139
0
30 Nov 2020
ERIC: Extracting Relations Inferred from Convolutions
ERIC: Extracting Relations Inferred from ConvolutionsAsian Conference on Computer Vision (ACCV), 2020
Joe Townsend
Theodoros Kasioumis
Hiroya Inakoshi
NAIFAtt
210
16
0
19 Oct 2020
Learning a functional control for high-frequency finance
Learning a functional control for high-frequency finance
Laura Leal
Mathieu Laurière
Charles-Albert Lehalle
AIFin
168
23
0
17 Jun 2020
Explainable Artificial Intelligence: a Systematic Review
Explainable Artificial Intelligence: a Systematic Review
Giulia Vilone
Luca Longo
XAI
758
308
0
29 May 2020
Distilling neural networks into skipgram-level decision lists
Distilling neural networks into skipgram-level decision lists
Madhumita Sushil
Simon Suster
Walter Daelemans
FAtt
282
0
0
14 May 2020
Evaluating Explanation Methods for Neural Machine Translation
Evaluating Explanation Methods for Neural Machine TranslationAnnual Meeting of the Association for Computational Linguistics (ACL), 2020
Jierui Li
Lemao Liu
Huayang Li
Guanlin Li
Guoping Huang
Shuming Shi
239
28
0
04 May 2020
How do Decisions Emerge across Layers in Neural Models? Interpretation
  with Differentiable Masking
How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable MaskingConference on Empirical Methods in Natural Language Processing (EMNLP), 2020
Nicola De Cao
Michael Schlichtkrull
Wilker Aziz
Ivan Titov
277
92
0
30 Apr 2020
Explainable Deep Learning: A Field Guide for the Uninitiated
Explainable Deep Learning: A Field Guide for the UninitiatedJournal of Artificial Intelligence Research (JAIR), 2020
Gabrielle Ras
Ning Xie
Marcel van Gerven
Derek Doran
AAMLXAI
576
440
0
30 Apr 2020
Sequential Interpretability: Methods, Applications, and Future Direction
  for Understanding Deep Learning Models in the Context of Sequential Data
Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data
B. Shickel
Parisa Rashidi
AI4TS
273
22
0
27 Apr 2020
Self-Attention Attribution: Interpreting Information Interactions Inside
  Transformer
Self-Attention Attribution: Interpreting Information Interactions Inside Transformer
Y. Hao
Li Dong
Furu Wei
Ke Xu
ViT
499
279
0
23 Apr 2020
Distance and Equivalence between Finite State Machines and Recurrent
  Neural Networks: Computational results
Distance and Equivalence between Finite State Machines and Recurrent Neural Networks: Computational results
Reda Marzouk
C. D. L. Higuera
246
8
0
01 Apr 2020
CheXplain: Enabling Physicians to Explore and UnderstandData-Driven,
  AI-Enabled Medical Imaging Analysis
CheXplain: Enabling Physicians to Explore and UnderstandData-Driven, AI-Enabled Medical Imaging AnalysisInternational Conference on Human Factors in Computing Systems (CHI), 2020
Yao Xie
Melody Chen
David Kao
Ge Gao
Xiang Ánthony' Chen
530
144
0
15 Jan 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies,
  Opportunities and Challenges toward Responsible AI
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIInformation Fusion (Inf. Fusion), 2019
Alejandro Barredo Arrieta
Natalia Díaz Rodríguez
Javier Del Ser
Adrien Bennetot
Siham Tabik
...
S. Gil-Lopez
Daniel Molina
Richard Benjamins
Raja Chatila
Francisco Herrera
XAI
1.2K
8,083
0
22 Oct 2019
Interpretations are useful: penalizing explanations to align neural
  networks with prior knowledge
Interpretations are useful: penalizing explanations to align neural networks with prior knowledgeInternational Conference on Machine Learning (ICML), 2019
Laura Rieger
Chandan Singh
W. James Murdoch
Bin Yu
FAtt
475
247
0
30 Sep 2019
Interpretable and Steerable Sequence Learning via Prototypes
Interpretable and Steerable Sequence Learning via PrototypesKnowledge Discovery and Data Mining (KDD), 2019
Yao Ming
Panpan Xu
Huamin Qu
Liu Ren
AI4TS
264
162
0
23 Jul 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
284
178
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
179
54
0
27 Mar 2019
State-Regularized Recurrent Neural Networks
State-Regularized Recurrent Neural Networks
Cheng Wang
Mathias Niepert
232
44
0
25 Jan 2019
Interpretable machine learning: definitions, methods, and applications
Interpretable machine learning: definitions, methods, and applications
W. James Murdoch
Chandan Singh
Karl Kumbier
R. Abbasi-Asl
Bin Yu
XAIHAI
483
1,700
0
14 Jan 2019
Interpretable Deep Learning under Fire
Interpretable Deep Learning under Fire
Xinyang Zhang
Ningfei Wang
Hua Shen
S. Ji
Xiapu Luo
Ting Wang
AAMLAI4CE
354
192
0
03 Dec 2018
Learning Finite State Representations of Recurrent Policy Networks
Learning Finite State Representations of Recurrent Policy Networks
Anurag Koul
S. Greydanus
Alan Fern
225
93
0
29 Nov 2018
Persistence pays off: Paying Attention to What the LSTM Gating Mechanism
  Persists
Persistence pays off: Paying Attention to What the LSTM Gating Mechanism Persists
Giancarlo D. Salton
John D. Kelleher
KELMRALM
380
9
0
10 Oct 2018
Hierarchical interpretations for neural network predictions
Hierarchical interpretations for neural network predictions
Chandan Singh
W. James Murdoch
Bin Yu
276
159
0
14 Jun 2018
Towards Binary-Valued Gates for Robust LSTM Training
Towards Binary-Valued Gates for Robust LSTM Training
Zhuohan Li
Di He
Fei Tian
Wei-neng Chen
Tao Qin
Liwei Wang
Tie-Yan Liu
MQ
200
50
0
08 Jun 2018
Learning Device Models with Recurrent Neural Networks
Learning Device Models with Recurrent Neural Networks
John Clemens
86
2
0
21 May 2018
Explanation Methods in Deep Learning: Users, Values, Concerns and
  Challenges
Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges
Gabrielle Ras
Marcel van Gerven
W. Haselager
XAI
347
239
0
20 Mar 2018
Learning Memory Access Patterns
Learning Memory Access Patterns
Milad Hashemi
Kevin Swersky
Jamie A. Smith
Grant Ayers
Heiner Litz
Jichuan Chang
Christos Kozyrakis
Parthasarathy Ranganathan
172
231
0
06 Mar 2018
Understanding Recurrent Neural State Using Memory Signatures
Understanding Recurrent Neural State Using Memory Signatures
Skanda Koppula
K. Sim
K. K. Chin
291
2
0
11 Feb 2018
Evaluating neural network explanation methods using hybrid documents and
  morphological agreement
Evaluating neural network explanation methods using hybrid documents and morphological agreement
Nina Pörner
Benjamin Roth
Hinrich Schütze
299
9
0
19 Jan 2018
Beyond Word Importance: Contextual Decomposition to Extract Interactions
  from LSTMs
Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs
W. James Murdoch
Peter J. Liu
Bin Yu
398
218
0
16 Jan 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
260
13
0
16 Jan 2018
Extracting Automata from Recurrent Neural Networks Using Queries and
  Counterexamples
Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples
Gail Weiss
Yoav Goldberg
Eran Yahav
321
205
0
27 Nov 2017
Visualizing and Understanding Atari Agents
Visualizing and Understanding Atari Agents
S. Greydanus
Anurag Koul
Jonathan Dodge
Alan Fern
FAtt
498
390
0
31 Oct 2017
Understanding Hidden Memories of Recurrent Neural Networks
Understanding Hidden Memories of Recurrent Neural NetworksIEEE Conference on Visual Analytics Science and Technology (VAST), 2017
Yao Ming
Shaozu Cao
Ruixiang Zhang
Zerui Li
Yuanzhe Chen
Yangqiu Song
Huamin Qu
HAI
211
222
0
30 Oct 2017
An Empirical Evaluation of Rule Extraction from Recurrent Neural
  Networks
An Empirical Evaluation of Rule Extraction from Recurrent Neural Networks
Qinglong Wang
Kaixuan Zhang
Alexander Ororbia
Masashi Sugiyama
Xue Liu
C. Lee Giles
372
66
0
29 Sep 2017
Explaining Recurrent Neural Network Predictions in Sentiment Analysis
Explaining Recurrent Neural Network Predictions in Sentiment Analysis
L. Arras
G. Montavon
K. Müller
Wojciech Samek
FAtt
369
382
0
22 Jun 2017
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