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2003.12537
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Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning
27 March 2020
Andreas Kirsch
Clare Lyle
Y. Gal
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Papers citing
"Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning"
13 / 13 papers shown
Towards Understanding Variants of Invariant Risk Minimization through the Lens of Calibration
Kotaro Yoshida
Hiroki Naganuma
452
4
0
31 Jan 2024
Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression
International Conference on Learning Representations (ICLR), 2023
I. Butakov
Alexander Tolmachev
S. Malanchuk
A. Neopryatnaya
Alexey Frolov
K. Andreev
333
20
0
13 May 2023
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility
IEEE Transactions on Information Forensics and Security (IEEE TIFS), 2022
Behrooz Razeghi
Flavio du Pin Calmon
Deniz Gunduz
Svyatoslav Voloshynovskiy
217
23
0
11 Jul 2022
Compressing Features for Learning with Noisy Labels
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Yingyi Chen
S. Hu
Xin Shen
C. Ai
Johan A. K. Suykens
NoLa
206
23
0
27 Jun 2022
Optimal Randomized Approximations for Matrix based Renyi's Entropy
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Yuxin Dong
Tieliang Gong
Shujian Yu
Chen Li
274
12
0
16 May 2022
A Note on "Assessing Generalization of SGD via Disagreement"
Andreas Kirsch
Y. Gal
FedML
UQCV
227
19
0
03 Feb 2022
Conditional entropy minimization principle for learning domain invariant representation features
International Conference on Pattern Recognition (ICPR), 2022
Thuan Q. Nguyen
Boyang Lyu
Prakash Ishwar
matthias. scheutz
Shuchin Aeron
OOD
281
8
0
25 Jan 2022
A Closer Look at the Adversarial Robustness of Information Bottleneck Models
I. Korshunova
David Stutz
Alexander A. Alemi
Olivia Wiles
Sven Gowal
167
4
0
12 Jul 2021
A Practical & Unified Notation for Information-Theoretic Quantities in ML
Andreas Kirsch
Y. Gal
226
7
0
22 Jun 2021
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
Neural Information Processing Systems (NeurIPS), 2021
Kartik Ahuja
Ethan Caballero
Dinghuai Zhang
Jean-Christophe Gagnon-Audet
Yoshua Bengio
Ioannis Mitliagkas
Irina Rish
OOD
345
336
0
11 Jun 2021
Deep Deterministic Uncertainty: A Simple Baseline
Computer Vision and Pattern Recognition (CVPR), 2021
Jishnu Mukhoti
Andreas Kirsch
Joost R. van Amersfoort
Juil Sock
Y. Gal
UD
UQCV
PER
BDL
580
238
0
23 Feb 2021
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation
International Conference on Learning Representations (ICLR), 2021
Alexandre Ramé
Matthieu Cord
FedML
328
60
0
14 Jan 2021
Action and Perception as Divergence Minimization
Danijar Hafner
Pedro A. Ortega
Jimmy Ba
Thomas Parr
Karl J. Friston
N. Heess
344
60
0
03 Sep 2020
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