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Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few
  Labels

Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels

21 February 2023
Zebin You
Yong Zhong
Fan Bao
Jiacheng Sun
Chongxuan Li
Jun Zhu
    DiffM
    VLM
ArXivPDFHTML

Papers citing "Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels"

15 / 15 papers shown
Title
Unsupervised Learning for Class Distribution Mismatch
Unsupervised Learning for Class Distribution Mismatch
Pan Du
Wangbo Zhao
Xinai Lu
Nian Liu
Z. Li
...
Suyun Zhao
H. Chen
Cuiping Li
Kai Wang
Yang You
26
0
0
11 May 2025
DIVE: Inverting Conditional Diffusion Models for Discriminative Tasks
DIVE: Inverting Conditional Diffusion Models for Discriminative Tasks
Yinqi Li
Hong Chang
Ruibing Hou
Shiguang Shan
Xilin Chen
DiffM
55
0
0
24 Apr 2025
Dual Conditional Diffusion Models for Sequential Recommendation
Dual Conditional Diffusion Models for Sequential Recommendation
Hongtao Huang
Chengkai Huang
Xiaojun Chang
Wen Hu
Lina Yao
Julian McAuley
Lina Yao
DiffM
42
2
0
29 Oct 2024
AI-Generated Images as Data Source: The Dawn of Synthetic Era
AI-Generated Images as Data Source: The Dawn of Synthetic Era
Zuhao Yang
Fangneng Zhan
Kunhao Liu
Muyu Xu
Shijian Lu
EGVM
31
18
0
03 Oct 2023
Equivariant Energy-Guided SDE for Inverse Molecular Design
Equivariant Energy-Guided SDE for Inverse Molecular Design
Fan Bao
Min Zhao
Zhongkai Hao
Pei‐Yun Li
Chongxuan Li
Jun Zhu
DiffM
187
63
0
30 Sep 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications
Diffusion Models: A Comprehensive Survey of Methods and Applications
Ling Yang
Zhilong Zhang
Yingxia Shao
Shenda Hong
Runsheng Xu
Yue Zhao
Wentao Zhang
Bin Cui
Ming-Hsuan Yang
DiffM
MedIm
224
1,302
0
02 Sep 2022
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
Yidong Wang
Hao Chen
Qiang Heng
Wenxin Hou
Yue Fan
...
Marios Savvides
T. Shinozaki
Bhiksha Raj
Bernt Schiele
Xing Xie
185
258
0
15 May 2022
StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets
StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets
Axel Sauer
Katja Schwarz
Andreas Geiger
182
489
0
01 Feb 2022
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
305
7,434
0
11 Nov 2021
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo
  Labeling
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
Bowen Zhang
Yidong Wang
Wenxin Hou
Hao Wu
Jindong Wang
Manabu Okumura
T. Shinozaki
AAML
226
862
0
15 Oct 2021
Unsupervised Selective Labeling for More Effective Semi-Supervised
  Learning
Unsupervised Selective Labeling for More Effective Semi-Supervised Learning
Xudong Wang
Long Lian
Stella X. Yu
186
33
0
06 Oct 2021
Instance-Conditioned GAN
Instance-Conditioned GAN
Arantxa Casanova
Marlene Careil
Jakob Verbeek
M. Drozdzal
Adriana Romero Soriano
GAN
204
132
0
10 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
314
5,775
0
29 Apr 2021
Meta Pseudo Labels
Meta Pseudo Labels
Hieu H. Pham
Zihang Dai
Qizhe Xie
Minh-Thang Luong
Quoc V. Le
VLM
253
656
0
23 Mar 2020
There Are Many Consistent Explanations of Unlabeled Data: Why You Should
  Average
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average
Ben Athiwaratkun
Marc Finzi
Pavel Izmailov
A. Wilson
199
243
0
14 Jun 2018
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