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. 2003.02037
  4. Cited By
Uncertainty Estimation Using a Single Deep Deterministic Neural Network

Uncertainty Estimation Using a Single Deep Deterministic Neural Network

4 March 2020
Joost R. van Amersfoort
Lewis Smith
Yee Whye Teh
Y. Gal
    UQCV
    BDL
ArXivPDFHTML

Papers citing "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"

16 / 16 papers shown
Title
Improving Semi-supervised Deep Learning by using Automatic Thresholding
  to Deal with Out of Distribution Data for COVID-19 Detection using Chest
  X-ray Images
Improving Semi-supervised Deep Learning by using Automatic Thresholding to Deal with Out of Distribution Data for COVID-19 Detection using Chest X-ray Images
Isaac Benavides-Mata
Saul Calderon-Ramirez
11
3
0
03 Nov 2022
Distributional Gaussian Processes Layers for Out-of-Distribution
  Detection
Distributional Gaussian Processes Layers for Out-of-Distribution Detection
S. Popescu
D. Sharp
James H. Cole
Konstantinos Kamnitsas
Ben Glocker
OOD
21
0
0
27 Jun 2022
Towards OOD Detection in Graph Classification from Uncertainty
  Estimation Perspective
Towards OOD Detection in Graph Classification from Uncertainty Estimation Perspective
Gleb Bazhenov
Sergei Ivanov
Maxim Panov
Alexey Zaytsev
Evgeny Burnaev
UQCV
23
9
0
21 Jun 2022
Distinction Maximization Loss: Efficiently Improving Out-of-Distribution
  Detection and Uncertainty Estimation by Replacing the Loss and Calibrating
Distinction Maximization Loss: Efficiently Improving Out-of-Distribution Detection and Uncertainty Estimation by Replacing the Loss and Calibrating
David Macêdo
Cleber Zanchettin
Teresa B Ludermir
UQCV
20
4
0
12 May 2022
Dealing with Distribution Mismatch in Semi-supervised Deep Learning for
  Covid-19 Detection Using Chest X-ray Images: A Novel Approach Using Feature
  Densities
Dealing with Distribution Mismatch in Semi-supervised Deep Learning for Covid-19 Detection Using Chest X-ray Images: A Novel Approach Using Feature Densities
Saul Calderon-Ramirez
Shengxiang-Yang
David Elizondo
Armaghan Moemeni
OOD
28
24
0
17 Aug 2021
The Promises and Pitfalls of Deep Kernel Learning
The Promises and Pitfalls of Deep Kernel Learning
Sebastian W. Ober
C. Rasmussen
Mark van der Wilk
UQCV
BDL
21
107
0
24 Feb 2021
DEUP: Direct Epistemic Uncertainty Prediction
DEUP: Direct Epistemic Uncertainty Prediction
Salem Lahlou
Moksh Jain
Hadi Nekoei
V. Butoi
Paul Bertin
Jarrid Rector-Brooks
Maksym Korablyov
Yoshua Bengio
PER
UQLM
UQCV
UD
200
81
0
16 Feb 2021
Advances in Electron Microscopy with Deep Learning
Advances in Electron Microscopy with Deep Learning
Jeffrey M. Ede
27
2
0
04 Jan 2021
A case for new neural network smoothness constraints
A case for new neural network smoothness constraints
Mihaela Rosca
T. Weber
A. Gretton
S. Mohamed
AAML
17
48
0
14 Dec 2020
The Hidden Uncertainty in a Neural Networks Activations
The Hidden Uncertainty in a Neural Networks Activations
Janis Postels
Hermann Blum
Yannick Strümpler
César Cadena
Roland Siegwart
Luc Van Gool
Federico Tombari
UQCV
22
22
0
05 Dec 2020
Feature Space Singularity for Out-of-Distribution Detection
Feature Space Singularity for Out-of-Distribution Detection
Haiwen Huang
Zhihan Li
Lulu Wang
Sishuo Chen
Bin Dong
Xinyu Zhou
OODD
20
65
0
30 Nov 2020
Depth Uncertainty in Neural Networks
Depth Uncertainty in Neural Networks
Javier Antorán
J. Allingham
José Miguel Hernández-Lobato
UQCV
OOD
BDL
22
100
0
15 Jun 2020
SAMBA: Safe Model-Based & Active Reinforcement Learning
SAMBA: Safe Model-Based & Active Reinforcement Learning
Alexander I. Cowen-Rivers
Daniel Palenicek
Vincent Moens
Mohammed Abdullah
Aivar Sootla
Jun Wang
Haitham Bou-Ammar
13
44
0
12 Jun 2020
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in
  Gaussian Process Hybrid Deep Networks
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks
John Bradshaw
A. G. Matthews
Zoubin Ghahramani
BDL
AAML
60
171
0
08 Jul 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
270
5,660
0
05 Dec 2016
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
261
9,134
0
06 Jun 2015
1