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. 2012.03082
  4. Cited By
The Hidden Uncertainty in a Neural Networks Activations

The Hidden Uncertainty in a Neural Networks Activations

5 December 2020
Janis Postels
Hermann Blum
Yannick Strümpler
César Cadena
Roland Siegwart
Luc Van Gool
Federico Tombari
    UQCV
ArXivPDFHTML

Papers citing "The Hidden Uncertainty in a Neural Networks Activations"

6 / 6 papers shown
Title
Beyond Confidence: Reliable Models Should Also Consider Atypicality
Beyond Confidence: Reliable Models Should Also Consider Atypicality
Mert Yuksekgonul
Linjun Zhang
James Y. Zou
Carlos Guestrin
25
20
0
29 May 2023
Robust Fusion for Bayesian Semantic Mapping
Robust Fusion for Bayesian Semantic Mapping
David Morilla-Cabello
Lorenzo Mur-Labadia
Ruben Martinez-Cantin
Eduardo Montijano
31
11
0
14 Mar 2023
Are generative deep models for novelty detection truly better?
Are generative deep models for novelty detection truly better?
V. Škvára
Tomás Pevný
Václav Smídl
31
38
0
13 Jul 2018
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
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
176
3,260
0
09 Jun 2012
1