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. 1901.05657
  4. Cited By
Certainty Driven Consistency Loss on Multi-Teacher Networks for
  Semi-Supervised Learning

Certainty Driven Consistency Loss on Multi-Teacher Networks for Semi-Supervised Learning

17 January 2019
Lu Liu
R. Tan
ArXivPDFHTML

Papers citing "Certainty Driven Consistency Loss on Multi-Teacher Networks for Semi-Supervised Learning"

7 / 7 papers shown
Title
Linear Projections of Teacher Embeddings for Few-Class Distillation
Linear Projections of Teacher Embeddings for Few-Class Distillation
Noel Loo
Fotis Iliopoulos
Wei Hu
Erik Vee
30
0
0
30 Sep 2024
Enhancing MR Image Segmentation with Realistic Adversarial Data
  Augmentation
Enhancing MR Image Segmentation with Realistic Adversarial Data Augmentation
Chia-Ju Chen
C. Qin
Cheng Ouyang
Zeju Li
Shuo Wang
Huaqi Qiu
Liang Chen
G. Tarroni
Wenjia Bai
Daniel Rueckert
GAN
MedIm
62
40
0
07 Aug 2021
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
208
243
0
14 Jun 2018
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
270
1,275
0
06 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,675
0
05 Dec 2016
Bayesian Convolutional Neural Networks with Bernoulli Approximate
  Variational Inference
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Y. Gal
Zoubin Ghahramani
UQCV
BDL
202
745
0
06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,145
0
06 Jun 2015
1