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1905.13472
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Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness
31 May 2019
A. Malinin
Mark J. F. Gales
UQCV
AAML
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Papers citing
"Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness"
40 / 40 papers shown
Title
Dataset Distillation with Probabilistic Latent Features
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Sarah Cechnicka
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Peter Schüffler
Bernhard Kainz
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47
0
0
10 May 2025
Subjective Logic Encodings
Jake Vasilakes
Chrysoula Zerva
Sophia Ananiadou
48
0
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17 Feb 2025
CoDiff: Conditional Diffusion Model for Collaborative 3D Object Detection
zhe Huang
Shuo Wang
Yunhong Wang
Lei Wang
DiffM
164
0
0
17 Feb 2025
Out-of-Distribution Detection using Synthetic Data Generation
Momin Abbas
Muneeza Azmat
R. Horesh
Mikhail Yurochkin
47
1
0
05 Feb 2025
Reducing Aleatoric and Epistemic Uncertainty through Multi-modal Data Acquisition
Arthur Hoarau
Benjamin Quost
Sébastien Destercke
Willem Waegeman
UQCV
UD
PER
72
0
0
30 Jan 2025
Latent Space Chain-of-Embedding Enables Output-free LLM Self-Evaluation
Yiming Wang
Pei Zhang
Baosong Yang
Derek F. Wong
Rui-cang Wang
LRM
50
4
0
17 Oct 2024
Adversarial Safety-Critical Scenario Generation using Naturalistic Human Driving Priors
Kunkun Hao
Yonggang Luo
Wen Cui
Yuqiao Bai
Jucheng Yang
Songyang Yan
Yuxi Pan
Zijiang Yang
AAML
30
17
0
06 Aug 2024
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression
Xuanlong Yu
Gianni Franchi
Jindong Gu
Emanuel Aldea
UQCV
16
4
0
17 Aug 2023
Function-Space Regularization for Deep Bayesian Classification
J. Lin
Joe Watson
Pascal Klink
Jan Peters
UQCV
BDL
38
1
0
12 Jul 2023
Block-local learning with probabilistic latent representations
David Kappel
Khaleelulla Khan Nazeer
Cabrel Teguemne Fokam
Christian Mayr
Anand Subramoney
24
4
0
24 May 2023
Non-Parametric Outlier Synthesis
Leitian Tao
Xuefeng Du
Xiaojin Zhu
Yixuan Li
OODD
28
98
0
06 Mar 2023
Tailoring Language Generation Models under Total Variation Distance
Haozhe Ji
Pei Ke
Zhipeng Hu
Rongsheng Zhang
Minlie Huang
28
18
0
26 Feb 2023
Post-hoc Uncertainty Learning using a Dirichlet Meta-Model
Maohao Shen
Yuheng Bu
P. Sattigeri
S. Ghosh
Subhro Das
G. Wornell
UQCV
OOD
BDL
13
31
0
14 Dec 2022
Distribution-based Emotion Recognition in Conversation
Wen Wu
C. Zhang
P. Woodland
21
4
0
09 Nov 2022
Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures?
Lisa Wimmer
Yusuf Sale
Paul Hofman
Bern Bischl
Eyke Hüllermeier
PER
UD
36
64
0
07 Sep 2022
OpenCon: Open-world Contrastive Learning
Yiyou Sun
Yixuan Li
VLM
SSL
DRL
52
39
0
04 Aug 2022
Effective Out-of-Distribution Detection in Classifier Based on PEDCC-Loss
Qiuyu Zhu
Guohui Zheng
Yingying Yan
OODD
14
8
0
10 Apr 2022
Self-Distribution Distillation: Efficient Uncertainty Estimation
Yassir Fathullah
Mark J. F. Gales
UQCV
19
11
0
15 Mar 2022
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation
Viktor Bengs
Eyke Hüllermeier
Willem Waegeman
EDL
UQCV
UD
24
36
0
11 Mar 2022
Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors
Wen Wu
C. Zhang
Xixin Wu
P. Woodland
48
14
0
08 Mar 2022
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers
Deebul Nair
Nico Hochgeschwender
Miguel A. Olivares-Mendez
OOD
30
7
0
03 Feb 2022
Improving robustness and calibration in ensembles with diversity regularization
H. A. Mehrtens
Camila González
Anirban Mukhopadhyay
UQCV
19
7
0
26 Jan 2022
Provable Guarantees for Understanding Out-of-distribution Detection
Peyman Morteza
Yixuan Li
OODD
30
86
0
01 Dec 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification
Maximilian Stadler
Bertrand Charpentier
Simon Geisler
Daniel Zügner
Stephan Günnemann
UQCV
BDL
41
80
0
26 Oct 2021
Generalized Out-of-Distribution Detection: A Survey
Jingkang Yang
Kaiyang Zhou
Yixuan Li
Ziwei Liu
185
879
0
21 Oct 2021
Deep Classifiers with Label Noise Modeling and Distance Awareness
Vincent Fortuin
Mark Collier
F. Wenzel
J. Allingham
J. Liu
Dustin Tran
Balaji Lakshminarayanan
Jesse Berent
Rodolphe Jenatton
E. Kokiopoulou
UQCV
34
11
0
06 Oct 2021
A Survey of Uncertainty in Deep Neural Networks
J. Gawlikowski
Cedrique Rovile Njieutcheu Tassi
Mohsin Ali
Jongseo Lee
Matthias Humt
...
R. Roscher
Muhammad Shahzad
Wen Yang
R. Bamler
Xiaoxiang Zhu
BDL
UQCV
OOD
41
1,111
0
07 Jul 2021
Being a Bit Frequentist Improves Bayesian Neural Networks
Agustinus Kristiadi
Matthias Hein
Philipp Hennig
BDL
UQCV
20
15
0
18 Jun 2021
Provably Robust Detection of Out-of-distribution Data (almost) for free
Alexander Meinke
Julian Bitterwolf
Matthias Hein
OODD
30
22
0
08 Jun 2021
DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference
Jiyang Xie
Zhanyu Ma
Jing-Hao Xue
Guoqiang Zhang
Jun Guo
BDL
27
11
0
17 Nov 2020
Failure Prediction by Confidence Estimation of Uncertainty-Aware Dirichlet Networks
Theodoros Tsiligkaridis
UQCV
22
7
0
19 Oct 2020
Uncertainty in Gradient Boosting via Ensembles
Aleksei Ustimenko
Liudmila Prokhorenkova
A. Malinin
UQCV
28
94
0
18 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts
Bertrand Charpentier
Daniel Zügner
Stephan Günnemann
UQCV
UD
EDL
BDL
25
169
0
16 Jun 2020
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data
Yen-Chang Hsu
Yilin Shen
Hongxia Jin
Z. Kira
OODD
24
558
0
26 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks
Agustinus Kristiadi
Matthias Hein
Philipp Hennig
BDL
UQCV
33
277
0
24 Feb 2020
Being Bayesian about Categorical Probability
Taejong Joo
U. Chung
Minji Seo
UQCV
BDL
25
58
0
19 Feb 2020
Ensemble Distribution Distillation
A. Malinin
Bruno Mlodozeniec
Mark J. F. Gales
UQCV
27
230
0
30 Apr 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,661
0
05 Dec 2016
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,837
0
08 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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