ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2101.07563
  4. Cited By
Using StyleGAN for Visual Interpretability of Deep Learning Models on
  Medical Images

Using StyleGAN for Visual Interpretability of Deep Learning Models on Medical Images

19 January 2021
K. Schutte
O. Moindrot
P. Hérent
Jean-Baptiste Schiratti
S. Jégou
    FAtt
    MedIm
ArXivPDFHTML

Papers citing "Using StyleGAN for Visual Interpretability of Deep Learning Models on Medical Images"

13 / 13 papers shown
Title
OWT: A Foundational Organ-Wise Tokenization Framework for Medical Imaging
OWT: A Foundational Organ-Wise Tokenization Framework for Medical Imaging
Sifan Song
Siyeop Yoon
Pengfei Jin
Sekeun Kim
Matthew Tivnan
...
Zhiliang Lyu
Dufan Wu
Ning Guo
Xiang Li
Quanzheng Li
OOD
ViT
64
0
0
08 May 2025
Counterfactual Explanations for Medical Image Classification and
  Regression using Diffusion Autoencoder
Counterfactual Explanations for Medical Image Classification and Regression using Diffusion Autoencoder
Matan Atad
D. Schinz
Hendrik Moeller
Robert Graf
Benedikt Wiestler
Daniel Rueckert
Nassir Navab
Jan S. Kirschke
Matthias Keicher
CML
DiffM
MedIm
42
3
0
02 Aug 2024
DiffExplainer: Unveiling Black Box Models Via Counterfactual Generation
DiffExplainer: Unveiling Black Box Models Via Counterfactual Generation
Yingying Fang
Shuang Wu
Zihao Jin
Caiwen Xu
Shiyi Wang
Simon Walsh
Guang Yang
MedIm
39
4
0
21 Jun 2024
Identifying Spurious Correlations using Counterfactual Alignment
Identifying Spurious Correlations using Counterfactual Alignment
Joseph Paul Cohen
Louis Blankemeier
Akshay S. Chaudhari
CML
55
1
0
01 Dec 2023
Diffusion Visual Counterfactual Explanations
Diffusion Visual Counterfactual Explanations
Maximilian Augustin
Valentyn Boreiko
Francesco Croce
Matthias Hein
DiffM
BDL
32
68
0
21 Oct 2022
Visual Interpretable and Explainable Deep Learning Models for Brain
  Tumor MRI and COVID-19 Chest X-ray Images
Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images
Yusuf Brima
M. Atemkeng
FAtt
MedIm
29
0
0
01 Aug 2022
Sparse Visual Counterfactual Explanations in Image Space
Sparse Visual Counterfactual Explanations in Image Space
Valentyn Boreiko
Maximilian Augustin
Francesco Croce
Philipp Berens
Matthias Hein
BDL
CML
30
26
0
16 May 2022
AUC Maximization in the Era of Big Data and AI: A Survey
AUC Maximization in the Era of Big Data and AI: A Survey
Tianbao Yang
Yiming Ying
38
179
0
28 Mar 2022
Mining the manifolds of deep generative models for multiple
  data-consistent solutions of ill-posed tomographic imaging problems
Mining the manifolds of deep generative models for multiple data-consistent solutions of ill-posed tomographic imaging problems
Sayantan Bhadra
Umberto Villa
M. Anastasio
MedIm
28
3
0
10 Feb 2022
Deep AUC Maximization for Medical Image Classification: Challenges and
  Opportunities
Deep AUC Maximization for Medical Image Classification: Challenges and Opportunities
Tianbao Yang
30
3
0
01 Nov 2021
Transparency of Deep Neural Networks for Medical Image Analysis: A
  Review of Interpretability Methods
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods
Zohaib Salahuddin
Henry C. Woodruff
A. Chatterjee
Philippe Lambin
18
302
0
01 Nov 2021
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to
  Counterfactual Generation for Chest X-rays
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays
Joseph Paul Cohen
Rupert Brooks
Sovann En
Evan Zucker
Anuj Pareek
M. Lungren
Akshay S. Chaudhari
FAtt
MedIm
37
4
0
18 Feb 2021
A Style-Based Generator Architecture for Generative Adversarial Networks
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras
S. Laine
Timo Aila
294
10,354
0
12 Dec 2018
1