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Deep pNML: Predictive Normalized Maximum Likelihood for Deep Neural
  Networks

Deep pNML: Predictive Normalized Maximum Likelihood for Deep Neural Networks

28 April 2019
Koby Bibas
Yaniv Fogel
M. Feder
    BDL
ArXivPDFHTML

Papers citing "Deep pNML: Predictive Normalized Maximum Likelihood for Deep Neural Networks"

4 / 4 papers shown
Title
Collaborative Image Understanding
Collaborative Image Understanding
Koby Bibas
Oren Sar Shalom
Dietmar Jannach
VLM
24
2
0
21 Oct 2022
Beyond Ridge Regression for Distribution-Free Data
Beyond Ridge Regression for Distribution-Free Data
Koby Bibas
M. Feder
22
0
0
17 Jun 2022
A New Look at an Old Problem: A Universal Learning Approach to Linear
  Regression
A New Look at an Old Problem: A Universal Learning Approach to Linear Regression
Koby Bibas
Yaniv Fogel
M. Feder
11
34
0
12 May 2019
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
289
9,167
0
06 Jun 2015
1