Using explainability to design physics-aware CNNs for solving subsurface
inverse problems

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Using explainability to design physics-aware CNNs for solving subsurface inverse problems

16 November 2022

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Papers citing "Using explainability to design physics-aware CNNs for solving subsurface inverse problems"

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Title
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction Melkamu Mersha Khang Lam Joseph Wood Ali AlShami Jugal Kalita XAI AI4TS 281 34 0 30 Aug 2024
A Frequency-Velocity CNN for Developing Near-Surface 2D Vs Images from Linear-Array, Active-Source Wavefield Measurements Aser Abbas J. Vantassel B. Cox Krishna Kumar J. Crocker 30 9 0 19 Jul 2022
Solving Inverse Problems With Deep Neural Networks -- Robustness Included? Martin Genzel Jan Macdonald M. März AAML OOD 54 107 0 09 Nov 2020
Progressive transfer learning for low frequency data prediction in full waveform inversion Wenyi Hu Yuchen Jin Xuqing Wu Jiefu Chen AI4CE 27 34 0 20 Dec 2019
Explainable artificial intelligence model to predict acute critical illness from electronic health records S. Lauritsen Mads Kristensen Mathias Vassard Olsen Morten Skaarup Larsen K. M. Lauritsen Marianne Johansson Jørgensen Jeppe Lange B. Thiesson 56 302 0 03 Dec 2019
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks Mehdi Neshat Zifan Wang Bradley Alexander Fan Yang Zijian Zhang Sirui Ding Markus Wagner Xia Hu FAtt 93 1,073 0 03 Oct 2019
XRAI: Better Attributions Through Regions A. Kapishnikov Tolga Bolukbasi Fernanda Viégas Michael Terry FAtt XAI 62 212 0 06 Jun 2019
Deep-learning inversion: a next generation seismic velocity-model building method Fangshu Yang Jianwei Ma 63 390 0 17 Feb 2019
Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks Tobias Hinz Nicolás Navarro-Guerrero S. Magg S. Wermter 69 105 0 19 Jul 2018
Confounding variables can degrade generalization performance of radiological deep learning models J. Zech Marcus A. Badgeley Manway Liu A. Costa J. Titano Eric K. Oermann OOD 85 1,180 0 02 Jul 2018
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning Pranav Rajpurkar Jeremy Irvin Kaylie Zhu Brandon Yang Hershel Mehta ... Aarti Bagul C. Langlotz K. Shpanskaya M. Lungren A. Ng LM&MA 85 2,709 0 14 Nov 2017
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks Aditya Chattopadhyay Anirban Sarkar Prantik Howlader V. Balasubramanian FAtt 112 2,306 0 30 Oct 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 203 3,881 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 193 6,018 0 04 Mar 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 324 20,086 0 07 Oct 2016
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems Martín Abadi Ashish Agarwal P. Barham E. Brevdo Zhiwen Chen ... Pete Warden Martin Wattenberg Martin Wicke Yuan Yu Xiaoqiang Zheng 282 11,150 0 14 Mar 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,033 0 16 Feb 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 253 9,338 0 14 Dec 2015
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 369 7,957 0 13 Jun 2012