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1906.02994
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Detecting Out-of-Distribution Inputs to Deep Generative Models Using Typicality
7 June 2019
Eric T. Nalisnick
Akihiro Matsukawa
Yee Whye Teh
Balaji Lakshminarayanan
OODD
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Papers citing
"Detecting Out-of-Distribution Inputs to Deep Generative Models Using Typicality"
50 / 52 papers shown
Resultant: Incremental Effectiveness on Likelihood for Unsupervised Out-of-Distribution Detection
Yewen Li
Chaojie Wang
Xiaobo Xia
Xu He
Ruyi An
Dong Li
Tongliang Liu
Bo An
Xinrun Wang
OODD
232
0
0
05 Sep 2024
Learning Non-Linear Invariants for Unsupervised Out-of-Distribution Detection
Lars Doorenbos
Raphael Sznitman
Pablo Márquez-Neila
319
1
0
04 Jul 2024
Nyström Kernel Stein Discrepancy
Florian Kalinke
Zoltan Szabo
Bharath K. Sriperumbudur
241
3
0
12 Jun 2024
Distribution Shift Inversion for Out-of-Distribution Prediction
Computer Vision and Pattern Recognition (CVPR), 2023
Runpeng Yu
Songhua Liu
Xingyi Yang
Xinchao Wang
OODD
187
26
0
14 Jun 2023
Unsupervised Out-of-Distribution Detection with Diffusion Inpainting
International Conference on Machine Learning (ICML), 2023
Zhenzhen Liu
Jinjie Zhou
Yufan Wang
Kilian Q. Weinberger
DiffM
390
56
0
20 Feb 2023
ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
International Conference on Machine Learning (ICML), 2023
Dongha Kim
Jaesung Hwang
Jongjin Lee
Kunwoong Kim
Yongdai Kim
OODD
294
3
0
11 Jan 2023
On the Connection of Generative Models and Discriminative Models for Anomaly Detection
Jingxuan Pang
Chunguang Li
156
1
0
16 Nov 2022
Falsehoods that ML researchers believe about OOD detection
Andi Zhang
Damon J. Wischik
OODD
272
7
0
23 Oct 2022
Pseudo-OOD training for robust language models
Dhanasekar Sundararaman
Nikhil Mehta
Lawrence Carin
164
0
0
17 Oct 2022
Provably Uncertainty-Guided Universal Domain Adaptation
Yifan Wang
Lin Zhang
Ran Song
Paul L. Rosin
Yibin Li
Wei Emma Zhang
OOD
UQCV
688
0
0
19 Sep 2022
Shaken, and Stirred: Long-Range Dependencies Enable Robust Outlier Detection with PixelCNN++
International Joint Conference on Artificial Intelligence (IJCAI), 2022
Barath Mohan Umapathi
Kushal Chauhan
Pradeep Shenoy
D. Sridharan
105
0
0
29 Aug 2022
Task Agnostic and Post-hoc Unseen Distribution Detection
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2022
Radhika Dua
Seong-sil Yang
Shouqing Yang
Edward Choi
OODD
234
11
0
26 Jul 2022
Exploiting Inter-Sample Affinity for Knowability-Aware Universal Domain Adaptation
International Journal of Computer Vision (IJCV), 2022
Yifan Wang
Lin Zhang
Ran Song
Hongliang Li
Lin Ma
Wei Emma Zhang
398
7
0
19 Jul 2022
Out-of-Distribution Detection with Class Ratio Estimation
Mingtian Zhang
Andi Zhang
Tim Z. Xiao
Yitong Sun
Jingyu Sun
OODD
195
7
0
08 Jun 2022
Variational Inference MPC using Normalizing Flows and Out-of-Distribution Projection
Thomas Power
Dmitry Berenson
200
41
0
10 May 2022
Learning by Erasing: Conditional Entropy based Transferable Out-Of-Distribution Detection
AAAI Conference on Artificial Intelligence (AAAI), 2022
Meng Xing
Zhiyong Feng
Yong Su
Changjae Oh
OODD
187
4
0
23 Apr 2022
Music Source Separation with Generative Flow
IEEE Signal Processing Letters (SPL), 2022
Ge Zhu
Jordan Darefsky
Fei Jiang
A. Selitskiy
Z. Duan
283
13
0
19 Apr 2022
Model-agnostic out-of-distribution detection using combined statistical tests
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Federico Bergamin
Pierre-Alexandre Mattei
Jakob Drachmann Havtorn
Hugo Senetaire
Hugo Schmutz
Lars Maaløe
Søren Hauberg
J. Frellsen
OODD
213
20
0
02 Mar 2022
Self-Supervised Anomaly Detection by Self-Distillation and Negative Sampling
International Conference on Artificial Neural Networks (ICANN), 2022
Nima Rafiee
Rahil Gholamipoorfard
Tim Kaiser
Simon Jaxy
Julius Ramakers
M. Kollmann
OODD
143
9
0
17 Jan 2022
Data Invariants to Understand Unsupervised Out-of-Distribution Detection
European Conference on Computer Vision (ECCV), 2021
Lars Doorenbos
Raphael Sznitman
Pablo Márquez-Neila
OODD
230
7
0
26 Nov 2021
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection
Chunjong Park
Anas Awadalla
Tadayoshi Kohno
Shwetak N. Patel
OOD
175
41
0
26 Oct 2021
Score-Based Generative Classifiers
Roland S. Zimmermann
Lukas Schott
Yang Song
Benjamin A. Dunn
David A. Klindt
DiffM
256
74
0
01 Oct 2021
On the Out-of-distribution Generalization of Probabilistic Image Modelling
Mingtian Zhang
Andi Zhang
Jingyu Sun
OODD
392
49
0
04 Sep 2021
Multi-Resolution Continuous Normalizing Flows
Vikram S. Voleti
Chris Finlay
Adam M. Oberman
Christopher Pal
382
6
0
15 Jun 2021
Detecting Anomalous Event Sequences with Temporal Point Processes
Neural Information Processing Systems (NeurIPS), 2021
Oleksandr Shchur
Ali Caner Turkmen
Tim Januschowski
Jan Gasthaus
Stephan Günnemann
AI4TS
178
13
0
08 Jun 2021
Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?
Zhisheng Xiao
Qing Yan
Y. Amit
OOD
UQCV
205
19
0
19 May 2021
Conditional Invertible Neural Networks for Diverse Image-to-Image Translation
German Conference on Pattern Recognition (DAGM), 2021
Lynton Ardizzone
Jakob Kruse
Carsten T. Lüth
Niels Bracher
Carsten Rother
Ullrich Kothe
245
38
0
05 May 2021
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization
Computer Vision and Pattern Recognition (CVPR), 2021
Chun-Liang Li
Kihyuk Sohn
Chang Jo Kim
Tomas Pfister
SSL
UQCV
238
1,022
0
08 Apr 2021
Testing for Typicality with Respect to an Ensemble of Learned Distributions
F. Laine
Claire Tomlin
129
0
0
11 Nov 2020
Learning and Evaluating Representations for Deep One-class Classification
Kihyuk Sohn
Chun-Liang Li
Chang Jo Kim
Minho Jin
Tomas Pfister
SSL
320
228
0
04 Nov 2020
Bigeminal Priors Variational auto-encoder
Xuming Ran
Mingkun Xu
Qi Xu
Huihui Zhou
Quanying Liu
139
3
0
05 Oct 2020
A Unifying Review of Deep and Shallow Anomaly Detection
Proceedings of the IEEE (Proc. IEEE), 2020
Lukas Ruff
Jacob R. Kauffmann
Robert A. Vandermeulen
G. Montavon
Wojciech Samek
Matthias Kirchler
Thomas G. Dietterich
Klaus-Robert Muller
UQCV
603
934
0
24 Sep 2020
Generative Classifiers as a Basis for Trustworthy Image Classification
Radek Mackowiak
Lynton Ardizzone
Ullrich Kothe
Carsten Rother
217
4
0
29 Jul 2020
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances
Neural Information Processing Systems (NeurIPS), 2020
Jihoon Tack
Sangwoo Mo
Jongheon Jeong
Jinwoo Shin
OODD
312
678
0
16 Jul 2020
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimation
Neural Networks (NN), 2020
Xuming Ran
Mingkun Xu
Lingrui Mei
Qi Xu
Quanying Liu
OODD
UQCV
298
60
0
16 Jul 2020
Efficient Learning of Generative Models via Finite-Difference Score Matching
Tianyu Pang
Kun Xu
Chongxuan Li
Yang Song
Stefano Ermon
Jun Zhu
DiffM
289
62
0
07 Jul 2020
Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features
R. Schirrmeister
Yuxuan Zhou
T. Ball
Dan Zhang
UQCV
392
93
0
18 Jun 2020
Density of States Estimation for Out-of-Distribution Detection
Warren Morningstar
Cusuh Ham
Andrew Gallagher
Balaji Lakshminarayanan
Alexander A. Alemi
Joshua V. Dillon
OODD
278
92
0
16 Jun 2020
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
Polina Kirichenko
Pavel Izmailov
A. Wilson
OODD
307
313
0
15 Jun 2020
NADS: Neural Architecture Distribution Search for Uncertainty Awareness
International Conference on Machine Learning (ICML), 2020
Randy Ardywibowo
Shahin Boluki
Xinyu Gong
Zinan Lin
Xiaoning Qian
UQCV
152
19
0
11 Jun 2020
Solving Inverse Problems with a Flow-based Noise Model
International Conference on Machine Learning (ICML), 2020
Jay Whang
Qi Lei
A. Dimakis
301
41
0
18 Mar 2020
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
Neural Information Processing Systems (NeurIPS), 2020
Zhisheng Xiao
Qing Yan
Y. Amit
OODD
390
214
0
06 Mar 2020
Detecting Out-of-Distribution Examples with In-distribution Examples and Gram Matrices
Chandramouli Shama Sastry
Sageev Oore
OODD
206
55
0
28 Dec 2019
Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection
Erik A. Daxberger
José Miguel Hernández-Lobato
UQCV
400
66
0
11 Dec 2019
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
International Conference on Learning Representations (ICLR), 2019
Will Grathwohl
Kuan-Chieh Wang
J. Jacobsen
David Duvenaud
Mohammad Norouzi
Kevin Swersky
VLM
503
604
0
06 Dec 2019
Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations
Computer Vision and Pattern Recognition (CVPR), 2019
Sven Gowal
Chongli Qin
Po-Sen Huang
taylan. cemgil
Krishnamurthy Dvijotham
Timothy A. Mann
Pushmeet Kohli
AAML
OOD
240
58
0
06 Dec 2019
Novelty Detection Via Blurring
International Conference on Learning Representations (ICLR), 2019
Sung-Ik Choi
Sae-Young Chung
UQCV
251
37
0
27 Nov 2019
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models
AAAI Conference on Artificial Intelligence (AAAI), 2019
Tong Che
Xiaofeng Liu
Site Li
Yubin Ge
Ruixiang Zhang
Caiming Xiong
Yoshua Bengio
424
54
0
18 Nov 2019
Likelihood Assignment for Out-of-Distribution Inputs in Deep Generative Models is Sensitive to Prior Distribution Choice
Ryo Kamoi
Kei Kobayashi
111
2
0
15 Nov 2019
Unsupervised Out-of-Distribution Detection with Batch Normalization
Jiaming Song
Yang Song
Stefano Ermon
OODD
111
23
0
21 Oct 2019
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