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1411.5908
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Understanding image representations by measuring their equivariance and equivalence
21 November 2014
Karel Lenc
Andrea Vedaldi
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Papers citing
"Understanding image representations by measuring their equivariance and equivalence"
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Title
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Invariance Measures for Neural Networks
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Domenec Puig-Valls
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Understanding the Inner Workings of Language Models Through Representation Dissimilarity
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Charles Godfrey
Nicholas Konz
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Revisiting Data Augmentation for Rotational Invariance in Convolutional Neural Networks
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Coloring Deep CNN Layers with Activation Hue Loss
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Distilling Influences to Mitigate Prediction Churn in Graph Neural Networks
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02 Oct 2023
Investigating Shift Equivalence of Convolutional Neural Networks in Industrial Defect Segmentation
Yunsheng Tian
Jieliang Luo
Yichen Li
Zhengtao Zhang
Hui Li
72
4
0
29 Sep 2023
Improving Equivariance in State-of-the-Art Supervised Depth and Normal Predictors
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Anand Bhattad
Yu-Xiong Wang
David Forsyth
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0
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Policy Stitching: Learning Transferable Robot Policies
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Easop Lee
Zachary I. Bell
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Flow Factorized Representation Learning
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Thomas Anderson Keller
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130
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Mode Combinability: Exploring Convex Combinations of Permutation Aligned Models
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Péter Korösi-Szabó
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Gergely Papp
D. Varga
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57
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Semantic Equivariant Mixup
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Tianchi Xie
Bing Wu
Qinghua Hu
Changqing Zhang
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129
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PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
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Shashank Shekhar
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106
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On genuine invariance learning without weight-tying
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A. Sepliarskaia
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67
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Going Beyond Linear Mode Connectivity: The Layerwise Linear Feature Connectivity
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Yongyi Yang
Xiaojiang Yang
Junchi Yan
Wei Hu
104
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17 Jul 2023
Large-Scale Person Detection and Localization using Overhead Fisheye Cameras
Lu Yang
Liulei Li
Xueshi Xin
Yifan Sun
Q. Song
Wenguan Wang
101
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17 Jul 2023
Substance or Style: What Does Your Image Embedding Know?
Cyrus Rashtchian
Charles Herrmann
Chun-Sung Ferng
Ayan Chakrabarti
Dilip Krishnan
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Da-Cheng Juan
Andrew Tomkins
57
6
0
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Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency
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Constantin Ulrich
Hyunjin Park
David Zimmerer
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Michael Baumgartner
Klaus H. Maier-Hein
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66
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Stitched ViTs are Flexible Vision Backbones
Zizheng Pan
Jing Liu
Haoyu He
Jianfei Cai
Bohan Zhuang
53
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Restore Translation Using Equivariant Neural Networks
Yihan Wang
Lijia Yu
Xiao-Shan Gao
54
0
0
29 Jun 2023
3D molecule generation by denoising voxel grids
Pedro H. O. Pinheiro
Joshua Rackers
J. Kleinhenz
Michael R. Maser
Omar Mahmood
Andrew Watkins
Stephen Ra
Vishnu Sresht
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DiffM
106
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Scale-Rotation-Equivariant Lie Group Convolution Neural Networks (Lie Group-CNNs)
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Yang Xu
Hui Li
63
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Investigating how ReLU-networks encode symmetries
Georg Bökman
Fredrik Kahl
67
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Text-To-Concept (and Back) via Cross-Model Alignment
Mazda Moayeri
Keivan Rezaei
Maziar Sanjabi
Soheil Feizi
CLIP
75
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0
10 May 2023
Similarity of Neural Network Models: A Survey of Functional and Representational Measures
Max Klabunde
Tobias Schumacher
M. Strohmaier
Florian Lemmerich
183
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10 May 2023
What Affects Learned Equivariance in Deep Image Recognition Models?
Robert-Jan Bruintjes
Tomasz Motyka
Jan van Gemert
114
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05 Apr 2023
Self-Supervised Multimodal Learning: A Survey
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Oisin Mac Aodha
Timothy M. Hospedales
SSL
125
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DeDA: Deep Directed Accumulator
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Rongguang Wang
Renjiu Hu
Jinwei Zhang
Jiahao Nick Li
MedIm
72
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Eliciting Latent Predictions from Transformers with the Tuned Lens
Nora Belrose
Zach Furman
Logan Smith
Danny Halawi
Igor V. Ostrovsky
Lev McKinney
Stella Biderman
Jacob Steinhardt
111
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A General Theory of Correct, Incorrect, and Extrinsic Equivariance
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Jung Yeon Park
Mingxi Jia
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Robert Platt
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85
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Bootstrapping Parallel Anchors for Relative Representations
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Marco Fumero
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Emanuele Rodolà
82
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Analyzing Populations of Neural Networks via Dynamical Model Embedding
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Felipe Hernández
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David Sussillo
100
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27 Feb 2023
Stress and Adaptation: Applying Anna Karenina Principle in Deep Learning for Image Classification
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Hanna Antson
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O. Shimmi
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22 Feb 2023
Oriented Object Detection in Optical Remote Sensing Images using Deep Learning: A Survey
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Zi Wang
Zhang Li
Ang Su
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Qifeng Yu
ObjD
211
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Stitchable Neural Networks
Zizheng Pan
Jianfei Cai
Bohan Zhuang
102
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Lorentz Equivariant Model for Knowledge-Enhanced Hyperbolic Collaborative Filtering
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Weihao Yu
Ruzhong Xie
Jing Xiao
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82
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Referential communication in heterogeneous communities of pre-trained visual deep networks
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Model Stitching and Visualization How GAN Generators can Invert Networks in Real-Time
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StitchNet: Composing Neural Networks from Pre-Trained Fragments
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Marcus Z. Comiter
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H. T. Kung
98
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Deep Incubation: Training Large Models by Divide-and-Conquering
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Haojun Jiang
Yu Cao
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94
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Task Discovery: Finding the Tasks that Neural Networks Generalize on
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Andrei Filatov
Teresa Yeo
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Amir Zamir
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134
10
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Internal Representations of Vision Models Through the Lens of Frames on Data Manifolds
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Grayson Jorgenson
Davis Brown
Charles Godfrey
Tegan H. Emerson
129
2
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Do Neural Networks Trained with Topological Features Learn Different Internal Representations?
Sarah McGuire
Shane Jackson
Tegan H. Emerson
Henry Kvinge
45
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EquiMod: An Equivariance Module to Improve Self-Supervised Learning
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Mathieu Lefort
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71
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Reliability of CKA as a Similarity Measure in Deep Learning
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Stefan Horoi
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Guillaume Lajoie
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Eugene Belilovsky
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145
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The Robustness Limits of SoTA Vision Models to Natural Variation
Mark Ibrahim
Q. Garrido
Ari S. Morcos
Diane Bouchacourt
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Deep Model Reassembly
Xingyi Yang
Zhou Daquan
Songhua Liu
Jingwen Ye
Xinchao Wang
MoMe
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GULP: a prediction-based metric between representations
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George Stepaniants
Philippe Rigollet
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LieGG: Studying Learned Lie Group Generators
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A. Sepliarskaia
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