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. 2110.09246
  4. Cited By
Single Layer Predictive Normalized Maximum Likelihood for
  Out-of-Distribution Detection

Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection

18 October 2021
Koby Bibas
M. Feder
Tal Hassner
    OODD
ArXivPDFHTML

Papers citing "Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection"

8 / 8 papers shown
Title
Reflexive Guidance: Improving OoDD in Vision-Language Models via Self-Guided Image-Adaptive Concept Generation
Reflexive Guidance: Improving OoDD in Vision-Language Models via Self-Guided Image-Adaptive Concept Generation
Seulbi Lee
J. Kim
Sangheum Hwang
LRM
114
0
0
19 Oct 2024
Beyond Ridge Regression for Distribution-Free Data
Beyond Ridge Regression for Distribution-Free Data
Koby Bibas
M. Feder
11
0
0
17 Jun 2022
Generalized Out-of-Distribution Detection: A Survey
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang
Kaiyang Zhou
Yixuan Li
Ziwei Liu
185
875
0
21 Oct 2021
Offline Model-Based Optimization via Normalized Maximum Likelihood
  Estimation
Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation
Justin Fu
Sergey Levine
OffRL
66
46
0
16 Feb 2021
Uncertainty aware and explainable diagnosis of retinal disease
Uncertainty aware and explainable diagnosis of retinal disease
Amitojdeep Singh
S. Sengupta
M. Rasheed
Varadharajan Jayakumar
Vasudevan Lakshminarayanan
BDL
27
21
0
26 Jan 2021
Learning Rotation Invariant Features for Cryogenic Electron Microscopy
  Image Reconstruction
Learning Rotation Invariant Features for Cryogenic Electron Microscopy Image Reconstruction
Koby Bibas
Gili Weiss-Dicker
Dana Cohen
Noa Cahan
H. Greenspan
12
7
0
10 Jan 2021
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
285
9,136
0
06 Jun 2015
1