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Cautious Deep Learning

Cautious Deep Learning

24 May 2018
Yotam Hechtlinger
Barnabás Póczós
Larry A. Wasserman
ArXivPDFHTML

Papers citing "Cautious Deep Learning"

17 / 17 papers shown
Title
Conformal Prediction: A Data Perspective
Conformal Prediction: A Data Perspective
Xiaofan Zhou
Baiting Chen
Yu Gui
Lu Cheng
77
3
0
09 Oct 2024
Building a stable classifier with the inflated argmax
Building a stable classifier with the inflated argmax
Jake A. Soloff
Rina Foygel Barber
Rebecca Willett
88
2
0
22 May 2024
Towards Certification of Uncertainty Calibration under Adversarial Attacks
Towards Certification of Uncertainty Calibration under Adversarial Attacks
Cornelius Emde
Francesco Pinto
Thomas Lukasiewicz
Philip H. S. Torr
Adel Bibi
AAML
40
0
0
22 May 2024
Conformal inference is (almost) free for neural networks trained with
  early stopping
Conformal inference is (almost) free for neural networks trained with early stopping
Zi-Chen Liang
Yan Zhou
Matteo Sesia
BDL
18
10
0
27 Jan 2023
Distribution-Free Finite-Sample Guarantees and Split Conformal
  Prediction
Distribution-Free Finite-Sample Guarantees and Split Conformal Prediction
Roel Hulsman
16
5
0
26 Oct 2022
Integrative conformal p-values for powerful out-of-distribution testing
  with labeled outliers
Integrative conformal p-values for powerful out-of-distribution testing with labeled outliers
Zi-Chen Liang
Matteo Sesia
Wenguang Sun
OODD
17
19
0
23 Aug 2022
Semantic uncertainty intervals for disentangled latent spaces
Semantic uncertainty intervals for disentangled latent spaces
S. Sankaranarayanan
Anastasios Nikolas Angelopoulos
Stephen Bates
Yaniv Romano
Phillip Isola
UQCV
23
21
0
20 Jul 2022
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning
Bat-Sheva Einbinder
Yaniv Romano
Matteo Sesia
Yanfei Zhou
UQCV
23
47
0
12 May 2022
Learning Optimal Conformal Classifiers
Learning Optimal Conformal Classifiers
David Stutz
Krishnamurthy Dvijotham
Dvijotham
A. Cemgil
Arnaud Doucet
16
79
0
18 Oct 2021
Learn then Test: Calibrating Predictive Algorithms to Achieve Risk
  Control
Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
Anastasios Nikolas Angelopoulos
Stephen Bates
Emmanuel J. Candès
Michael I. Jordan
Lihua Lei
95
125
0
03 Oct 2021
Combining Deep Learning and Verification for Precise Object Instance
  Detection
Combining Deep Learning and Verification for Precise Object Instance Detection
Siddharth Ancha
Junyu Nan
David Held
18
3
0
27 Dec 2019
Cryptocurrency Price Prediction and Trading Strategies Using Support
  Vector Machines
Cryptocurrency Price Prediction and Trading Strategies Using Support Vector Machines
David Zhao
Alessandro Rinaldo
C. Brookins
9
8
0
26 Nov 2019
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction
  to Concepts and Methods
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods
Eyke Hüllermeier
Willem Waegeman
PER
UD
11
1,352
0
21 Oct 2019
Density estimation in representation space to predict model uncertainty
Density estimation in representation space to predict model uncertainty
Tiago Ramalho
M. Corbalan
UQCV
BDL
6
37
0
20 Aug 2019
Rarely-switching linear bandits: optimization of causal effects for the
  real world
Rarely-switching linear bandits: optimization of causal effects for the real world
B. Lansdell
Sofia Triantafillou
Konrad Paul Kording
13
4
0
30 May 2019
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
281
5,833
0
08 Jul 2016
Cross-conformal predictors
Cross-conformal predictors
V. Vovk
118
196
0
03 Aug 2012
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