A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

7 October 2016

Papers citing "A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks"

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Title
Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation Jihun Yi Sungroh Yoon 42 383 0 29 Jun 2020
Not all Failure Modes are Created Equal: Training Deep Neural Networks for Explicable (Mis)Classification Alberto Olmo Sailik Sengupta S. Kambhampati 28 6 0 26 Jun 2020
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance Gagan Bansal Tongshuang Wu Joyce Zhou Raymond Fok Besmira Nushi Ece Kamar Marco Tulio Ribeiro Daniel S. Weld 42 584 0 26 Jun 2020
Supermasks in Superposition Mitchell Wortsman Vivek Ramanujan Rosanne Liu Aniruddha Kembhavi Mohammad Rastegari J. Yosinski Ali Farhadi SSL CLL 33 281 0 26 Jun 2020
Task-agnostic Out-of-Distribution Detection Using Kernel Density Estimation Ertunc Erdil K. Chaitanya Neerav Karani E. Konukoglu OODD 27 7 0 18 Jun 2020
Uncertainty in Gradient Boosting via Ensembles Aleksei Ustimenko Liudmila Prokhorenkova A. Malinin UQCV 28 94 0 18 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Wang Roger C. Grosse J. Jacobsen 23 93 0 16 Jun 2020
Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets Zhihui Shao Jianyi Yang Shaolei Ren OODD 35 11 0 16 Jun 2020
Detecting unusual input to neural networks Jörg Martin Clemens Elster AAML 17 7 0 15 Jun 2020
MixMOOD: A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures Saul Calderon-Ramirez Luis Oala J. Torrents-Barrena Shengxiang-Yang Armaghan Moemeni Wojciech Samek Miguel A. Molina-Cabello 33 10 0 14 Jun 2020
Towards Robust Pattern Recognition: A Review Xu-Yao Zhang Cheng-Lin Liu C. Suen OOD HAI 26 103 0 12 Jun 2020
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers S. Melacci Gabriele Ciravegna Angelo Sotgiu Ambra Demontis Battista Biggio Marco Gori Fabio Roli 22 14 0 06 Jun 2020
Few-Shot Open-Set Recognition using Meta-Learning Bo Liu Hao Kang Haoxiang Li G. Hua Nuno Vasconcelos BDL EDL 28 89 0 27 May 2020
Learning Global and Local Features of Normal Brain Anatomy for Unsupervised Abnormality Detection Kazuma Kobayashi Ryuichiro Hataya Y. Kurose Amina Bolatkan M. Miyake Hirokazu Watanabe Masamichi Takahashi J. Itami Tatsuya Harada Ryuji Hamamoto MedIm 11 1 0 26 May 2020
Interpreting Rate-Distortion of Variational Autoencoder and Using Model Uncertainty for Anomaly Detection Seonho Park George Adosoglou P. Pardalos DRL UQCV 34 16 0 05 May 2020
DQI: Measuring Data Quality in NLP Swaroop Mishra Anjana Arunkumar Bhavdeep Singh Sachdeva Chris Bryan Chitta Baral 36 30 0 02 May 2020
SCOUT: Self-aware Discriminant Counterfactual Explanations Pei Wang Nuno Vasconcelos FAtt 30 81 0 16 Apr 2020
Pretrained Transformers Improve Out-of-Distribution Robustness Dan Hendrycks Xiaoyuan Liu Eric Wallace Adam Dziedzic R. Krishnan D. Song OOD 21 430 0 13 Apr 2020
DeepStreamCE: A Streaming Approach to Concept Evolution Detection in Deep Neural Networks Lorraine Chambers M. Gaber Zahraa S Abdallah 21 4 0 08 Apr 2020
M2m: Imbalanced Classification via Major-to-minor Translation Jaehyung Kim Jongheon Jeong Jinwoo Shin 17 220 0 01 Apr 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 75 99 0 20 Mar 2020
Calibration of Pre-trained Transformers Shrey Desai Greg Durrett UQLM 248 290 0 17 Mar 2020
Anomalous Example Detection in Deep Learning: A Survey Saikiran Bulusu B. Kailkhura Bo Li P. Varshney D. Song AAML 28 47 0 16 Mar 2020
An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods Sanghyuk Chun Seong Joon Oh Sangdoo Yun Dongyoon Han Junsuk Choe Y. Yoo AAML OOD 345 53 0 09 Mar 2020
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks Marius Hobbhahn Agustinus Kristiadi Philipp Hennig BDL UQCV 78 32 0 02 Mar 2020
Unbiased Mean Teacher for Cross-domain Object Detection Jinhong Deng Wen Li Yuhua Chen Lixin Duan 79 287 0 02 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 908 0 02 Mar 2020
DROCC: Deep Robust One-Class Classification Sachin Goyal Aditi Raghunathan Moksh Jain H. Simhadri Prateek Jain VLM 28 161 0 28 Feb 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 23 6 0 28 Feb 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 24 561 0 26 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 38 277 0 24 Feb 2020
The Conditional Entropy Bottleneck Ian S. Fischer OOD 29 116 0 13 Feb 2020
Semi-Supervised Class Discovery Jeremy Nixon J. Liu David Berthelot 20 2 0 10 Feb 2020
OoDAnalyzer: Interactive Analysis of Out-of-Distribution Samples Changjian Chen Jun Yuan Yafeng Lu Yang Liu Hang Su Songtao Yuan Shixia Liu OODD 26 63 0 08 Feb 2020
Real-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems Feiyang Cai X. Koutsoukos OODD 123 75 0 28 Jan 2020
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence Kihyuk Sohn David Berthelot Chun-Liang Li Zizhao Zhang Nicholas Carlini E. D. Cubuk Alexey Kurakin Han Zhang Colin Raffel AAML 104 3,479 0 21 Jan 2020
Personalized Activity Recognition with Deep Triplet Embeddings D. Burns C. Whyne HAI 29 25 0 15 Jan 2020
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning Andreas Sedlmeier Thomas Gabor Thomy Phan Lenz Belzner Claudia Linnhoff-Popien 21 25 0 31 Dec 2019
TRADI: Tracking deep neural network weight distributions for uncertainty estimation Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch UQCV 26 51 0 24 Dec 2019
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 43 529 0 06 Dec 2019
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation Alireza Mehrtash W. Wells C. Tempany Purang Abolmaesumi Tina Kapur OOD FedML UQCV 24 265 0 29 Nov 2019
Detection and Mitigation of Rare Subclasses in Deep Neural Network Classifiers Colin Paterson R. Calinescu Chiara Picardi 38 4 0 28 Nov 2019
Scaling Out-of-Distribution Detection for Real-World Settings Dan Hendrycks Steven Basart Mantas Mazeika Andy Zou Joe Kwon Mohammadreza Mostajabi Jacob Steinhardt D. Song OODD 20 463 0 25 Nov 2019
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models Tong Che Xiaofeng Liu Site Li Yubin Ge Ruixiang Zhang Caiming Xiong Yoshua Bengio 38 52 0 18 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 21 104 0 13 Nov 2019
Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks Kira Maag Matthias Rottmann Hanno Gottschalk 29 34 0 12 Nov 2019
Fully Bayesian Recurrent Neural Networks for Safe Reinforcement Learning Matthew Benatan Edward O. Pyzer-Knapp BDL 24 6 0 08 Nov 2019
Confident Learning: Estimating Uncertainty in Dataset Labels Curtis G. Northcutt Lu Jiang Isaac L. Chuang NoLa 46 676 0 31 Oct 2019
Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer Output Vahdat Abdelzad Krzysztof Czarnecki Rick Salay Taylor Denouden Sachin Vernekar Buu Phan OODD 27 46 0 23 Oct 2019
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 87 1,359 0 21 Oct 2019