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A Practical & Unified Notation for Information-Theoretic Quantities in ML

A Practical & Unified Notation for Information-Theoretic Quantities in ML

Andreas Kirsch
Y. Gal
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Papers citing "A Practical & Unified Notation for Information-Theoretic Quantities in ML"

5 / 5 papers shown
Title
Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities
Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities
Andreas Kirsch
Y. Gal
FedML
22
21
0
01 Aug 2022
Marginal and Joint Cross-Entropies & Predictives for Online Bayesian Inference, Active Learning, and Active Sampling
Marginal and Joint Cross-Entropies & Predictives for Online Bayesian Inference, Active Learning, and Active Sampling
Andreas Kirsch
Jannik Kossen
Y. Gal
UQCV
BDL
50
3
0
18 May 2022
A Note on "Assessing Generalization of SGD via Disagreement"
A Note on "Assessing Generalization of SGD via Disagreement"
Andreas Kirsch
Y. Gal
FedML
UQCV
21
15
0
03 Feb 2022
Test Distribution-Aware Active Learning: A Principled Approach Against Distribution Shift and Outliers
Test Distribution-Aware Active Learning: A Principled Approach Against Distribution Shift and Outliers
Andreas Kirsch
Tom Rainforth
Y. Gal
OOD
TTA
24
22
0
22 Jun 2021
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