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Unveiling the Potential of Probabilistic Embeddings in Self-Supervised
  Learning

Unveiling the Potential of Probabilistic Embeddings in Self-Supervised Learning

27 October 2023
Denis Janiak
Jakub Binkowski
Piotr Bielak
Tomasz Kajdanowicz
    SSL
    UQCV
ArXivPDFHTML

Papers citing "Unveiling the Potential of Probabilistic Embeddings in Self-Supervised Learning"

4 / 4 papers shown
Title
Compressive Visual Representations
Compressive Visual Representations
Kuang-Huei Lee
Anurag Arnab
S. Guadarrama
John F. Canny
Ian S. Fischer
SSL
65
48
0
27 Sep 2021
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
317
5,775
0
29 Apr 2021
Probabilistic Embeddings for Cross-Modal Retrieval
Probabilistic Embeddings for Cross-Modal Retrieval
Sanghyuk Chun
Seong Joon Oh
Rafael Sampaio de Rezende
Yannis Kalantidis
Diane Larlus
UQCV
401
200
0
13 Jan 2021
ImageNet Large Scale Visual Recognition Challenge
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
296
39,194
0
01 Sep 2014
1