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Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models

16 June 2016

Viktoriya Krakovna

Finale Doshi-Velez

AI4CE

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Papers citing "Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models"

31 / 31 papers shown

Title
A Review of Multimodal Explainable Artificial Intelligence: Past, Present and Future Shilin Sun Wenbin An Feng Tian Fang Nan Qidong Liu Jing Liu N. Shah Ping Chen 208 9 0 18 Dec 2024
Generative learning for nonlinear dynamics William Gilpin AI4CE PINN 157 31 0 07 Nov 2023
AI for Investment: A Platform Disruption Mohammad Rasouli Ravi Chiruvolu Ali Risheh 64 4 0 06 Sep 2023
Hybrid hidden Markov LSTM for short-term traffic flow prediction Agnimitra Sengupta A. Das S. I. Guler BDL AI4TS 69 3 0 11 Jul 2023
Weighted Automata Extraction and Explanation of Recurrent Neural Networks for Natural Language Tasks Zeming Wei Xiyue Zhang Yihao Zhang Meng Sun 99 12 0 24 Jun 2023
BTPK-based interpretable method for NER tasks based on Talmudic Public Announcement Logic Yulin Chen Beishui Liao Bruno Bentzen Bo Yuan Zelai Yao Haixiao Chi D. Gabbay 83 1 0 24 Jan 2022
M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis Xingbo Wang Jianben He Zhihua Jin Muqiao Yang Yong Wang Huamin Qu 122 83 0 17 Jul 2021
Absolute Value Constraint: The Reason for Invalid Performance Evaluation Results of Neural Network Models for Stock Price Prediction Yi Wei 126 1 0 10 Jan 2021
MEME: Generating RNN Model Explanations via Model Extraction Dmitry Kazhdan B. Dimanov M. Jamnik Pietro Lio LRM 89 13 0 13 Dec 2020
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs Cheng Wang Carolin (Haas) Lawrence Mathias Niepert UQCV 74 10 0 24 Nov 2020
Scaling Hidden Markov Language Models Justin T. Chiu Alexander M. Rush BDL 147 25 0 09 Nov 2020
Towards Ground Truth Explainability on Tabular Data Brian Barr Ke Xu Claudio Silva E. Bertini Robert Reilly C. Bayan Bruss J. Wittenbach 130 7 0 20 Jul 2020
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity S. Udrescu A. Tan Jiahai Feng Orisvaldo Neto Tailin Wu Max Tegmark 180 209 0 18 Jun 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 180 396 0 30 Apr 2020
Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data B. Shickel Parisa Rashidi AI4TS 99 18 0 27 Apr 2020
Intelligence, physics and information -- the tradeoff between accuracy and simplicity in machine learning Tailin Wu 148 1 0 11 Jan 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI 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 543 6,721 0 22 Oct 2019
Powering Hidden Markov Model by Neural Network based Generative Models Dong Liu Antoine Honoré Saikat Chatterjee L. Rasmussen BDL 172 15 0 13 Oct 2019
Scalable Explanation of Inferences on Large Graphs Chao Chen Yuhang Liu Xi Zhang Sihong Xie 75 6 0 13 Aug 2019
Self-Attentive Hawkes Processes Qiang Zhang Aldo Lipani Ömer Kirnap Emine Yilmaz AI4TS 143 46 0 17 Jul 2019
Improving the Performance of the LSTM and HMM Model via Hybridization Larkin Liu Yu-Chung Lin Joshua Reid 154 9 0 09 Jul 2019
Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks Joshua J. Michalenko Ameesh Shah Abhinav Verma Richard G. Baraniuk Swarat Chaudhuri Ankit B. Patel AI4CE 136 22 0 27 Feb 2019
An Evaluation of the Human-Interpretability of Explanation Isaac Lage Emily Chen Jeffrey He Menaka Narayanan Been Kim Sam Gershman Finale Doshi-Velez FAtt XAI 195 164 0 31 Jan 2019
Evaluating the Ability of LSTMs to Learn Context-Free Grammars Luzi Sennhauser Robert C. Berwick 111 57 0 06 Nov 2018
Using Machine Learning Safely in Automotive Software: An Assessment and Adaption of Software Process Requirements in ISO 26262 Rick Salay Krzysztof Czarnecki 114 71 0 05 Aug 2018
Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections Xin Zhang Armando Solar-Lezama Rishabh Singh FAtt 134 63 0 21 Feb 2018
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks J. Uesato Brendan O'Donoghue Aaron van den Oord Pushmeet Kohli AAML 348 618 0 15 Feb 2018
Understanding Recurrent Neural State Using Memory Signatures Skanda Koppula K. Sim K. K. Chin 127 2 0 11 Feb 2018
Fibres of Failure: Classifying errors in predictive processes L. Carlsson Gunnar Carlsson Mikael Vejdemo-Johansson AI4CE 135 4 0 09 Feb 2018
How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation Menaka Narayanan Emily Chen Jeffrey He Been Kim S. Gershman Finale Doshi-Velez FAtt XAI 128 246 0 02 Feb 2018
Interpretable Recurrent Neural Networks Using Sequential Sparse Recovery Scott Wisdom Thomas Powers J. Pitton L. Atlas 113 36 0 22 Nov 2016