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. 2006.09273
  4. Cited By
Density of States Estimation for Out-of-Distribution Detection

Density of States Estimation for Out-of-Distribution Detection

16 June 2020
Warren Morningstar
Cusuh Ham
Andrew Gallagher
Balaji Lakshminarayanan
Alexander A. Alemi
Joshua V. Dillon
    OODD
ArXivPDFHTML

Papers citing "Density of States Estimation for Out-of-Distribution Detection"

18 / 18 papers shown
Title
DSDE: Using Proportion Estimation to Improve Model Selection for
  Out-of-Distribution Detection
DSDE: Using Proportion Estimation to Improve Model Selection for Out-of-Distribution Detection
Jingyao Geng
Yuan Zhang
Jiaqi Huang
Feng Xue
Falong Tan
Chuanlong Xie
Shumei Zhang
OODD
43
0
0
03 Nov 2024
Learning Non-Linear Invariants for Unsupervised Out-of-Distribution
  Detection
Learning Non-Linear Invariants for Unsupervised Out-of-Distribution Detection
Lars Doorenbos
Raphael Sznitman
Pablo Márquez-Neila
39
1
0
04 Jul 2024
Out-of-Distribution Detection with a Single Unconditional Diffusion
  Model
Out-of-Distribution Detection with a Single Unconditional Diffusion Model
Alvin Heng
Alexandre H. Thiery
Harold Soh
48
1
0
20 May 2024
Building One-class Detector for Anything: Open-vocabulary Zero-shot OOD
  Detection Using Text-image Models
Building One-class Detector for Anything: Open-vocabulary Zero-shot OOD Detection Using Text-image Models
Yunhao Ge
Jie Jessie Ren
Jiaping Zhao
Kaifeng Chen
Andrew Gallagher
Laurent Itti
Balaji Lakshminarayanan
VLM
ObjD
24
1
0
26 May 2023
A Comprehensive Review of Trends, Applications and Challenges In
  Out-of-Distribution Detection
A Comprehensive Review of Trends, Applications and Challenges In Out-of-Distribution Detection
Navid Ghassemi
E. F. Ersi
AAML
OODD
20
4
0
26 Sep 2022
Model-agnostic out-of-distribution detection using combined statistical
  tests
Model-agnostic out-of-distribution detection using combined statistical tests
Federico Bergamin
Pierre-Alexandre Mattei
Jakob Drachmann Havtorn
Hugo Senetaire
Hugo Schmutz
Lars Maaløe
Søren Hauberg
J. Frellsen
OODD
21
18
0
02 Mar 2022
Data Invariants to Understand Unsupervised Out-of-Distribution Detection
Data Invariants to Understand Unsupervised Out-of-Distribution Detection
Lars Doorenbos
Raphael Sznitman
Pablo Márquez-Neila
OODD
24
6
0
26 Nov 2021
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift
  Detection
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection
Chunjong Park
Anas Awadalla
Tadayoshi Kohno
Shwetak N. Patel
OOD
25
29
0
26 Oct 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node
  Classification
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification
Maximilian Stadler
Bertrand Charpentier
Simon Geisler
Daniel Zügner
Stephan Günnemann
UQCV
BDL
28
80
0
26 Oct 2021
On the Importance of Regularisation & Auxiliary Information in OOD
  Detection
On the Importance of Regularisation & Auxiliary Information in OOD Detection
John Mitros
Brian Mac Namee
21
2
0
15 Jul 2021
Test for non-negligible adverse shifts
Test for non-negligible adverse shifts
Vathy M. Kamulete
15
3
0
07 Jul 2021
Task-agnostic Continual Learning with Hybrid Probabilistic Models
Task-agnostic Continual Learning with Hybrid Probabilistic Models
Polina Kirichenko
Mehrdad Farajtabar
Dushyant Rao
Balaji Lakshminarayanan
Nir Levine
Ang Li
Huiyi Hu
A. Wilson
Razvan Pascanu
VLM
BDL
CLL
14
19
0
24 Jun 2021
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection
Jie Jessie Ren
Stanislav Fort
J. Liu
Abhijit Guha Roy
Shreyas Padhy
Balaji Lakshminarayanan
UQCV
33
216
0
16 Jun 2021
InFlow: Robust outlier detection utilizing Normalizing Flows
InFlow: Robust outlier detection utilizing Normalizing Flows
Nishant Kumar
Pia Hanfeld
Michael Hecht
Michael Bussmann
Stefan Gumhold
Nico Hoffmann
OODD
OOD
TPM
21
4
0
10 Jun 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
202
81
0
16 Feb 2021
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
27
22
0
05 Dec 2020
Probabilistic Autoencoder
Probabilistic Autoencoder
Vanessa Böhm
U. Seljak
UQCV
BDL
DRL
16
32
0
09 Jun 2020
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
1