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Inductive Bias of Deep Convolutional Networks through Pooling Geometry

Inductive Bias of Deep Convolutional Networks through Pooling Geometry

22 May 2016
Nadav Cohen
Amnon Shashua
ArXivPDFHTML

Papers citing "Inductive Bias of Deep Convolutional Networks through Pooling Geometry"

27 / 27 papers shown
Title
A Tensor Decomposition Perspective on Second-order RNNs
A Tensor Decomposition Perspective on Second-order RNNs
M. Lizaire
Michael Rizvi-Martel
Marawan Gamal Abdel Hameed
Guillaume Rabusseau
52
0
0
07 Jun 2024
Neural Redshift: Random Networks are not Random Functions
Neural Redshift: Random Networks are not Random Functions
Damien Teney
A. Nicolicioiu
Valentin Hartmann
Ehsan Abbasnejad
103
18
0
04 Mar 2024
Forecasting through deep learning and modal decomposition in two-phase
  concentric jets
Forecasting through deep learning and modal decomposition in two-phase concentric jets
L. Mata
Rodrigo Abadía-Heredia
Manuel López Martín
J. M. Pérez
S. L. Clainche
14
8
0
24 Dec 2022
On the Ability of Graph Neural Networks to Model Interactions Between
  Vertices
On the Ability of Graph Neural Networks to Model Interactions Between Vertices
Noam Razin
Tom Verbin
Nadav Cohen
23
10
0
29 Nov 2022
Plausible May Not Be Faithful: Probing Object Hallucination in
  Vision-Language Pre-training
Plausible May Not Be Faithful: Probing Object Hallucination in Vision-Language Pre-training
Wenliang Dai
Zihan Liu
Ziwei Ji
Dan Su
Pascale Fung
MLLM
VLM
32
62
0
14 Oct 2022
Frequency Dropout: Feature-Level Regularization via Randomized Filtering
Frequency Dropout: Feature-Level Regularization via Randomized Filtering
Mobarakol Islam
Ben Glocker
OOD
35
6
0
20 Sep 2022
Transformer Vs. MLP-Mixer: Exponential Expressive Gap For NLP Problems
Transformer Vs. MLP-Mixer: Exponential Expressive Gap For NLP Problems
D. Navon
A. Bronstein
MoE
38
0
0
17 Aug 2022
Implicit Regularization in Hierarchical Tensor Factorization and Deep
  Convolutional Neural Networks
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks
Noam Razin
Asaf Maman
Nadav Cohen
46
29
0
27 Jan 2022
iSegFormer: Interactive Segmentation via Transformers with Application
  to 3D Knee MR Images
iSegFormer: Interactive Segmentation via Transformers with Application to 3D Knee MR Images
Qin Liu
Zhenlin Xu
Yining Jiao
Marc Niethammer
ViT
MedIm
49
37
0
21 Dec 2021
Learning with convolution and pooling operations in kernel methods
Learning with convolution and pooling operations in kernel methods
Theodor Misiakiewicz
Song Mei
MLT
15
29
0
16 Nov 2021
The Inductive Bias of In-Context Learning: Rethinking Pretraining
  Example Design
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design
Yoav Levine
Noam Wies
Daniel Jannai
D. Navon
Yedid Hoshen
Amnon Shashua
AI4CE
35
36
0
09 Oct 2021
A Random CNN Sees Objects: One Inductive Bias of CNN and Its
  Applications
A Random CNN Sees Objects: One Inductive Bias of CNN and Its Applications
Yun Cao
Jianxin Wu
SSL
31
26
0
17 Jun 2021
Which transformer architecture fits my data? A vocabulary bottleneck in
  self-attention
Which transformer architecture fits my data? A vocabulary bottleneck in self-attention
Noam Wies
Yoav Levine
Daniel Jannai
Amnon Shashua
40
20
0
09 May 2021
Rethinking Spatial Dimensions of Vision Transformers
Rethinking Spatial Dimensions of Vision Transformers
Byeongho Heo
Sangdoo Yun
Dongyoon Han
Sanghyuk Chun
Junsuk Choe
Seong Joon Oh
ViT
362
564
0
30 Mar 2021
Efficient Feature Transformations for Discriminative and Generative
  Continual Learning
Efficient Feature Transformations for Discriminative and Generative Continual Learning
Vinay Kumar Verma
Kevin J Liang
Nikhil Mehta
Piyush Rai
Lawrence Carin
CLL
38
76
0
25 Mar 2021
Entangled q-Convolutional Neural Nets
Entangled q-Convolutional Neural Nets
V. Anagiannis
Miranda C. N. Cheng
16
5
0
06 Mar 2021
Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein
  Distance)
Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance)
Jan Stanczuk
Christian Etmann
L. Kreusser
Carola-Bibiane Schönlieb
GAN
16
48
0
02 Mar 2021
Exploring Complementary Strengths of Invariant and Equivariant
  Representations for Few-Shot Learning
Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
Mamshad Nayeem Rizve
Salman Khan
Fahad Shahbaz Khan
M. Shah
41
108
0
01 Mar 2021
Computational Separation Between Convolutional and Fully-Connected
  Networks
Computational Separation Between Convolutional and Fully-Connected Networks
Eran Malach
Shai Shalev-Shwartz
19
26
0
03 Oct 2020
Learning from Protein Structure with Geometric Vector Perceptrons
Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing
Stephan Eismann
Patricia Suriana
Raphael J. L. Townshend
R. Dror
GNN
3DV
25
471
0
03 Sep 2020
The Depth-to-Width Interplay in Self-Attention
The Depth-to-Width Interplay in Self-Attention
Yoav Levine
Noam Wies
Or Sharir
Hofit Bata
Amnon Shashua
30
45
0
22 Jun 2020
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Noam Razin
Nadav Cohen
24
155
0
13 May 2020
Weight Agnostic Neural Networks
Weight Agnostic Neural Networks
Adam Gaier
David R Ha
OOD
35
239
0
11 Jun 2019
Learning Relevant Features of Data with Multi-scale Tensor Networks
Learning Relevant Features of Data with Multi-scale Tensor Networks
Tayssir Doghri
25
137
0
31 Dec 2017
Tensor Networks for Dimensionality Reduction and Large-Scale
  Optimizations. Part 2 Applications and Future Perspectives
Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future Perspectives
A. Cichocki
Anh-Huy Phan
Qibin Zhao
Namgil Lee
Ivan Oseledets
Masashi Sugiyama
Danilo P. Mandic
26
295
0
30 Aug 2017
Analysis and Design of Convolutional Networks via Hierarchical Tensor
  Decompositions
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions
Nadav Cohen
Or Sharir
Yoav Levine
Ronen Tamari
David Yakira
Amnon Shashua
15
38
0
05 May 2017
Generalization Error of Invariant Classifiers
Generalization Error of Invariant Classifiers
Jure Sokolić
Raja Giryes
Guillermo Sapiro
M. Rodrigues
13
77
0
14 Oct 2016
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