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Enhancing Interpretability of Sparse Latent Representations with Class Information

Enhancing Interpretability of Sparse Latent Representations with Class Information

20 May 2025
Farshad Sangari Abiz
Reshad Hosseini
Babak N. Araabi
    DRL
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Papers citing "Enhancing Interpretability of Sparse Latent Representations with Class Information"

6 / 6 papers shown
Title
Generative Adversarial Networks
Generative Adversarial Networks
Gilad Cohen
Raja Giryes
GAN
143
30,069
0
01 Mar 2022
GLOWin: A Flow-based Invertible Generative Framework for Learning
  Disentangled Feature Representations in Medical Images
GLOWin: A Flow-based Invertible Generative Framework for Learning Disentangled Feature Representations in Medical Images
Aadhithya Sankar
Matthias Keicher
R. Eisawy
Abhijeet Parida
Franz MJ Pfister
Seong Tae Kim
Nassir Navab
OOD
DRL
MedIm
28
8
0
19 Mar 2021
Denoising Diffusion Probabilistic Models
Denoising Diffusion Probabilistic Models
Jonathan Ho
Ajay Jain
Pieter Abbeel
DiffM
292
17,550
0
19 Jun 2020
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
168
8,807
0
25 Aug 2017
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
538
21,613
0
22 May 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
582
16,828
0
16 Feb 2016
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