HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine Learning Models

12 February 2020

Huamin Qu

Papers citing "HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine Learning Models"

23 / 23 papers shown

Title
iGAiVA: Integrated Generative AI and Visual Analytics in a Machine Learning Workflow for Text Classification Yuanzhe Jin Adrian Carrasco-Revilla Min Chen VLM 89 1 0 24 Sep 2024
YOLOv4: Optimal Speed and Accuracy of Object Detection Alexey Bochkovskiy Chien-Yao Wang H. Liao VLM ObjD 176 12,301 0 23 Apr 2020
The What-If Tool: Interactive Probing of Machine Learning Models James Wexler Mahima Pushkarna Tolga Bolukbasi Martin Wattenberg F. Viégas Jimbo Wilson VLM 81 494 0 09 Jul 2019
Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations Fred Hohman Haekyu Park Caleb Robinson Duen Horng Chau FAtt 3DH HAI 55 218 0 04 Apr 2019
ColorNet: Investigating the importance of color spaces for image classification Shreyank N. Gowda C. Yuan 39 129 0 01 Feb 2019
GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation Minsuk Kahng Nikhil Thorat Duen Horng Chau F. Viégas Martin Wattenberg HAI GAN 55 173 0 05 Sep 2018
DeepTracker: Visualizing the Training Process of Convolutional Neural Networks Dongyu Liu Weiwei Cui Kai Jin Yuxiao Guo Huamin Qu HAI 45 35 0 26 Aug 2018
Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models Jiawei Zhang Yang Wang Piero Molino Lezhi Li D. Ebert FAtt 50 204 0 01 Aug 2018
The State of the Art in Integrating Machine Learning into Visual Analytics Alex Endert W. Ribarsky C. Turkay B. Wong I. Nabney Ignacio Díaz Blanco Fabrice Rossi 31 215 0 22 Feb 2018
Visual Interpretability for Deep Learning: a Survey Quanshi Zhang Song-Chun Zhu FaML HAI 144 822 0 02 Feb 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 242 1,849 0 30 Nov 2017
Understanding Hidden Memories of Recurrent Neural Networks Yao Ming Shaozu Cao Ruixiang Zhang Zerui Li Yuanzhe Chen Yangqiu Song Huamin Qu HAI 40 201 0 30 Oct 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 285 8,928 0 25 Aug 2017
Avoiding Discrimination through Causal Reasoning Niki Kilbertus Mateo Rojas-Carulla Giambattista Parascandolo Moritz Hardt Dominik Janzing Bernhard Schölkopf FaML CML 115 584 0 08 Jun 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 1.2K 20,900 0 17 Apr 2017
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models Minsuk Kahng Pierre Yves Andrews Aditya Kalro Duen Horng Chau HAI 75 324 0 06 Apr 2017
Achieving non-discrimination in prediction Lu Zhang Yongkai Wu Xintao Wu FaML 51 32 0 28 Feb 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 335 20,110 0 07 Oct 2016
Towards Better Analysis of Deep Convolutional Neural Networks Mengchen Liu Jiaxin Shi Zerui Li Chongxuan Li Jun Zhu Shixia Liu HAI 117 477 0 24 Apr 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 253 9,342 0 14 Dec 2015
Understanding Neural Networks Through Deep Visualization J. Yosinski Jeff Clune Anh Totti Nguyen Thomas J. Fuchs Hod Lipson FAtt AI4CE 126 1,875 0 22 Jun 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 254 4,681 0 21 Dec 2014
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 600 15,907 0 12 Nov 2013