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Intrinsic dimension of data representations in deep neural networks

Intrinsic dimension of data representations in deep neural networks

29 May 2019
A. Ansuini
Alessandro Laio
Jakob H. Macke
D. Zoccolan
    AI4CE
ArXivPDFHTML

Papers citing "Intrinsic dimension of data representations in deep neural networks"

14 / 64 papers shown
Title
Dataset Distillation with Infinitely Wide Convolutional Networks
Dataset Distillation with Infinitely Wide Convolutional Networks
Timothy Nguyen
Roman Novak
Lechao Xiao
Jaehoon Lee
DD
51
231
0
27 Jul 2021
Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering
Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering
Nairouz Mrabah
Mohamed Bouguessa
M. Touati
Riadh Ksantini
40
63
0
19 Jul 2021
Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction
  for Few-Shot Classification
Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification
Dong Lee
Sae-Young Chung
31
20
0
22 Jun 2021
Relative stability toward diffeomorphisms indicates performance in deep
  nets
Relative stability toward diffeomorphisms indicates performance in deep nets
Leonardo Petrini
Alessandro Favero
Mario Geiger
Matthieu Wyart
OOD
38
15
0
06 May 2021
On 1/n neural representation and robustness
On 1/n neural representation and robustness
Josue Nassar
Piotr A. Sokól
SueYeon Chung
K. Harris
Il Memming Park
AAML
OOD
24
23
0
08 Dec 2020
Generative Capacity of Probabilistic Protein Sequence Models
Generative Capacity of Probabilistic Protein Sequence Models
Francisco McGee
Quentin Novinger
R. Levy
Vincenzo Carnevale
A. Haldane
40
34
0
03 Dec 2020
Geometric compression of invariant manifolds in neural nets
Geometric compression of invariant manifolds in neural nets
J. Paccolat
Leonardo Petrini
Mario Geiger
Kevin Tyloo
Matthieu Wyart
MLT
60
34
0
22 Jul 2020
Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation
Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation
Jihun Yi
Sungroh Yoon
42
383
0
29 Jun 2020
The Gaussian equivalence of generative models for learning with shallow
  neural networks
The Gaussian equivalence of generative models for learning with shallow neural networks
Sebastian Goldt
Bruno Loureiro
Galen Reeves
Florent Krzakala
M. Mézard
Lenka Zdeborová
BDL
41
100
0
25 Jun 2020
Density-embedding layers: a general framework for adaptive receptive
  fields
Density-embedding layers: a general framework for adaptive receptive fields
Francesco Cicala
Luca Bortolussi
16
0
0
23 Jun 2020
What Do Neural Networks Learn When Trained With Random Labels?
What Do Neural Networks Learn When Trained With Random Labels?
Hartmut Maennel
Ibrahim M. Alabdulmohsin
Ilya O. Tolstikhin
R. Baldock
Olivier Bousquet
Sylvain Gelly
Daniel Keysers
FedML
48
87
0
18 Jun 2020
HERS: Homomorphically Encrypted Representation Search
HERS: Homomorphically Encrypted Representation Search
Joshua J. Engelsma
Anil K. Jain
Vishnu Boddeti
43
50
0
27 Mar 2020
Blessing of dimensionality at the edge
Blessing of dimensionality at the edge
I. Tyukin
Alexander N. Gorban
A. McEwan
Sepehr Meshkinfamfard
Lixin Tang
21
8
0
30 Sep 2019
Intrinsic dimension estimation for locally undersampled data
Intrinsic dimension estimation for locally undersampled data
Vittorio Erba
M. Gherardi
P. Rotondo
22
30
0
18 Jun 2019
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