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Pseudo-label Learning with Calibrated Confidence Using an Energy-based
  Model

Pseudo-label Learning with Calibrated Confidence Using an Energy-based Model

15 April 2024
Masahito Toba
Seiichi Uchida
Hideaki Hayashi
ArXivPDFHTML

Papers citing "Pseudo-label Learning with Calibrated Confidence Using an Energy-based Model"

5 / 5 papers shown
Title
Bridging Precision and Confidence: A Train-Time Loss for Calibrating
  Object Detection
Bridging Precision and Confidence: A Train-Time Loss for Calibrating Object Detection
Muhammad Akhtar Munir
Muhammad Haris Khan
Salman Khan
F. Khan
UQCV
32
15
0
25 Mar 2023
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D
  biomedical image classification
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification
Jiancheng Yang
Rui Shi
D. Wei
Zequan Liu
Lin Zhao
B. Ke
Hanspeter Pfister
Bingbing Ni
VLM
171
647
0
27 Oct 2021
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence
  Calibration
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration
Xiao Wang
Hongrui Liu
Chuan Shi
Cheng Yang
UQCV
109
113
0
29 Sep 2021
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label
  Selection Framework for Semi-Supervised Learning
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
Mamshad Nayeem Rizve
Kevin Duarte
Y. S. Rawat
M. Shah
223
509
0
15 Jan 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
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