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It's FLAN time! Summing feature-wise latent representations for interpretability

18 June 2021

An-phi Nguyen

María Rodríguez Martínez

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Papers citing "It's FLAN time! Summing feature-wise latent representations for interpretability"

38 / 38 papers shown

Title
TITAN: T Cell Receptor Specificity Prediction with Bimodal Attention Networks Anna Weber Jannis Born María Rodríguez Martínez 33 131 0 21 Apr 2021
TransFG: A Transformer Architecture for Fine-grained Recognition Ju He Jieneng Chen Shuai Liu Adam Kortylewski Cheng Yang Yutong Bai Changhu Wang ViT 82 389 0 14 Mar 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 670 41,430 0 22 Oct 2020
On quantitative aspects of model interpretability An-phi Nguyen María Rodríguez Martínez 49 115 0 15 Jul 2020
iCapsNets: Towards Interpretable Capsule Networks for Text Classification Zhengyang Wang Xia Hu Shuiwang Ji 38 11 0 16 May 2020
Neural Additive Models: Interpretable Machine Learning with Neural Nets Rishabh Agarwal Levi Melnick Nicholas Frosst Xuezhou Zhang Ben Lengerich R. Caruana Geoffrey E. Hinton 92 420 0 29 Apr 2020
Building and Interpreting Deep Similarity Models Oliver Eberle Jochen Büttner Florian Kräutli K. Müller Matteo Valleriani G. Montavon 56 58 0 11 Mar 2020
One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency Kacper Sokol Peter A. Flach 39 176 0 27 Jan 2020
RandAugment: Practical automated data augmentation with a reduced search space E. D. Cubuk Barret Zoph Jonathon Shlens Quoc V. Le MQ 250 3,502 0 30 Sep 2019
MonoNet: Towards Interpretable Models by Learning Monotonic Features An-phi Nguyen María Rodríguez Martínez FAtt 55 13 0 30 Sep 2019
InterpretML: A Unified Framework for Machine Learning Interpretability Harsha Nori Samuel Jenkins Paul Koch R. Caruana AI4CE 153 488 0 19 Sep 2019
On the Variance of the Adaptive Learning Rate and Beyond Liyuan Liu Haoming Jiang Pengcheng He Weizhu Chen Xiaodong Liu Jianfeng Gao Jiawei Han ODL 289 1,907 0 08 Aug 2019
XLNet: Generalized Autoregressive Pretraining for Language Understanding Zhilin Yang Zihang Dai Yiming Yang J. Carbonell Ruslan Salakhutdinov Quoc V. Le AI4CE 236 8,447 0 19 Jun 2019
Towards Aggregating Weighted Feature Attributions Umang Bhatt Pradeep Ravikumar José M. F. Moura FAtt TDI 29 13 0 20 Jan 2019
Hierarchical Attentional Hybrid Neural Networks for Document Classification Jader Abreu Luis Fred David Macêdo Cleber Zanchettin 58 37 0 20 Jan 2019
Personalized explanation in machine learning: A conceptualization J. Schneider J. Handali XAI FAtt 52 17 0 03 Jan 2019
This Looks Like That: Deep Learning for Interpretable Image Recognition Chaofan Chen Oscar Li Chaofan Tao A. Barnett Jonathan Su Cynthia Rudin 246 1,188 0 27 Jun 2018
Towards Robust Interpretability with Self-Explaining Neural Networks David Alvarez-Melis Tommi Jaakkola MILM XAI 128 947 0 20 Jun 2018
Stronger generalization bounds for deep nets via a compression approach Sanjeev Arora Rong Ge Behnam Neyshabur Yi Zhang MLT AI4CE 89 643 0 14 Feb 2018
Generalization in Deep Learning Kenji Kawaguchi L. Kaelbling Yoshua Bengio ODL 97 460 0 16 Oct 2017
Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions Oscar Li Hao Liu Chaofan Chen Cynthia Rudin 178 592 0 13 Oct 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 250 4,273 0 22 Jun 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 730 132,363 0 12 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,002 0 22 May 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 193 6,018 0 04 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 405 3,813 0 28 Feb 2017
Investigating the influence of noise and distractors on the interpretation of neural networks Pieter-Jan Kindermans Kristof T. Schütt K. Müller Sven Dähne FAtt 74 125 0 22 Nov 2016
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Zhuowen Tu Kaiming He 522 10,347 0 16 Nov 2016
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 321 20,086 0 07 Oct 2016
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Zhiwen Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 908 6,796 0 26 Sep 2016
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 350 8,174 0 13 Aug 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,426 0 10 Dec 2015
Semi-supervised Sequence Learning Andrew M. Dai Quoc V. Le SSL 132 1,234 0 04 Nov 2015
Character-level Convolutional Networks for Text Classification Xiang Zhang Jiaqi Zhao Yann LeCun 268 6,130 0 04 Sep 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,312 0 22 Dec 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,595 0 01 Sep 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 314 7,316 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 595 15,902 0 12 Nov 2013