Concept Evolution in Deep Learning Training: A Unified Interpretation Framework and Discoveries

30 March 2022

Papers citing "Concept Evolution in Deep Learning Training: A Unified Interpretation Framework and Discoveries"

8 / 8 papers shown

Title
Concept-Monitor: Understanding DNN training through individual neurons Mohammad Ali Khan Tuomas P. Oikarinen Tsui-Wei Weng 11 2 0 26 Apr 2023
Generalization Beyond Feature Alignment: Concept Activation-Guided Contrastive Learning Y. Liu Chris Xing Tian Haoliang Li Shiqi Wang 18 1 0 13 Nov 2022
NeuroMapper: In-browser Visualizer for Neural Network Training Zhiyan Zhou Kevin Li Haekyu Park Megan Dass Austin P. Wright Nilaksh Das Duen Horng Chau 3DH 13 2 0 22 Oct 2022
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan Ö. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 120 297 0 17 Oct 2019
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 261 10,196 0 16 Nov 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,878 0 15 Sep 2016
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 282 39,170 0 01 Sep 2014
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 228 31,150 0 16 Jan 2013