Harnessing the Power of Explanations for Incremental Training: A
LIME-Based Approach

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Harnessing the Power of Explanations for Incremental Training: A LIME-Based Approach

2 November 2022

Ashutosh Pandey

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Papers citing "Harnessing the Power of Explanations for Incremental Training: A LIME-Based Approach"

10 / 10 papers shown

Title
Utilizing Explainable AI for improving the Performance of Neural Networks Huawei Sun Lorenzo Servadei Hao Feng Michael Stephan Robert Wille Avik Santra 51 7 0 07 Oct 2022
Explain to Not Forget: Defending Against Catastrophic Forgetting with XAI Sami Ede Serop Baghdadlian Leander Weber A. Nguyen Dario Zanca Wojciech Samek Sebastian Lapuschkin CLL 53 8 0 04 May 2022
Continual Learning in Human Activity Recognition: an Empirical Analysis of Regularization Saurav Jha Martin Schiemer Juan Ye CLL 31 13 0 06 Jul 2020
Optimal Continual Learning has Perfect Memory and is NP-hard Jeremias Knoblauch Hisham Husain Tom Diethe CLL 125 105 0 09 Jun 2020
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 1,074 0 03 Oct 2019
Gradient Episodic Memory for Continual Learning David Lopez-Paz MarcÁurelio Ranzato VLM CLL 127 2,725 0 26 Jun 2017
Overcoming catastrophic forgetting in neural networks J. Kirkpatrick Razvan Pascanu Neil C. Rabinowitz J. Veness Guillaume Desjardins ... A. Grabska-Barwinska Demis Hassabis Claudia Clopath D. Kumaran R. Hadsell CLL 369 7,547 0 02 Dec 2016
Grad-CAM: Why did you say that? Ramprasaath R. Selvaraju Abhishek Das Ramakrishna Vedantam Michael Cogswell Devi Parikh Dhruv Batra FAtt 70 475 0 22 Nov 2016
The Mythos of Model Interpretability Zachary Chase Lipton FaML 183 3,706 0 10 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,027 0 16 Feb 2016