v1v2 (latest)

Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem

13 December 2018

Matthias Hein

Maksym Andriushchenko

Julian Bitterwolf

OODD

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Papers citing "Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem"

49 / 349 papers shown

Title
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks Keyulu Xu Mozhi Zhang Jingling Li S. Du Ken-ichi Kawarabayashi Stefanie Jegelka MLT 184 313 0 24 Sep 2020
Detection of Iterative Adversarial Attacks via Counter Attack Matthias Rottmann Kira Maag Mathis Peyron N. Krejić Hanno Gottschalk AAML 47 4 0 23 Sep 2020
Regularizing Attention Networks for Anomaly Detection in Visual Question Answering Doyup Lee Yeongjae Cheon Wook-Shin Han AAML OOD 44 16 0 21 Sep 2020
Adaptive Label Smoothing Ujwal Krothapalli A. Lynn Abbott 98 10 0 14 Sep 2020
A Survey on Assessing the Generalization Envelope of Deep Neural Networks: Predictive Uncertainty, Out-of-distribution and Adversarial Samples Julia Lust Alexandru Paul Condurache UQCV AAML AI4CE 31 8 0 21 Aug 2020
A General Framework For Detecting Anomalous Inputs to DNN Classifiers Jayaram Raghuram Varun Chandrasekaran S. Jha Suman Banerjee AAML 106 35 0 29 Jul 2020
Certifiably Adversarially Robust Detection of Out-of-Distribution Data Julian Bitterwolf Alexander Meinke Matthias Hein 65 9 0 16 Jul 2020
Nested Learning For Multi-Granular Tasks Raphaël Achddou J. Matias Di Martino Guillermo Sapiro 31 1 0 13 Jul 2020
Revisiting One-vs-All Classifiers for Predictive Uncertainty and Out-of-Distribution Detection in Neural Networks Shreyas Padhy Zachary Nado Jie Jessie Ren J. Liu Jasper Snoek Balaji Lakshminarayanan UQCV 88 47 0 10 Jul 2020
Soft Labeling Affects Out-of-Distribution Detection of Deep Neural Networks Doyup Lee Yeongjae Cheon 35 6 0 07 Jul 2020
ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining Jiefeng Chen Yixuan Li Xi Wu Yingyu Liang S. Jha OODD 102 140 0 26 Jun 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification F. Wenzel Jasper Snoek Dustin Tran Rodolphe Jenatton UQCV 117 212 0 24 Jun 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 290 453 0 17 Jun 2020
Revisiting Explicit Regularization in Neural Networks for Well-Calibrated Predictive Uncertainty Taejong Joo U. Chung BDL UQCV 34 0 0 11 Jun 2020
A t-distribution based operator for enhancing out of distribution robustness of neural network classifiers Niccolò Antonello Philip N. Garner 71 4 0 09 Jun 2020
Entropic Out-of-Distribution Detection: Seamless Detection of Unknown Examples David Macêdo T. I. Ren Cleber Zanchettin Adriano Oliveira Teresa B Ludermir OODD 58 25 0 07 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 88 15 0 06 Jun 2020
ReLU Code Space: A Basis for Rating Network Quality Besides Accuracy Natalia Shepeleva Werner Zellinger Michal Lewandowski Bernhard A. Moser 37 3 0 20 May 2020
A Review of Computer Vision Methods in Network Security Jiawei Zhao Rahat Masood Suranga Seneviratne AAML 52 48 0 07 May 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 231 2,073 0 16 Apr 2020
Robust Out-of-distribution Detection for Neural Networks Jiefeng Chen Yixuan Li Xi Wu Yingyu Liang S. Jha OODD 231 88 0 21 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 193 102 0 20 Mar 2020
Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation Yingda Xia Yi Zhang Fengze Liu Wei Shen Alan Yuille UQCV 94 153 0 18 Mar 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning Jize Zhang B. Kailkhura T. Y. Han UQCV 106 227 0 16 Mar 2020
No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting with Adversarial Attacks Siqi Liu A. Setio Florin-Cristian Ghesu Eli Gibson Sasa Grbic Bogdan Georgescu Dorin Comaniciu AAML OOD 117 40 0 08 Mar 2020
Dropout Strikes Back: Improved Uncertainty Estimation via Diversity Sampling Kirill Fedyanin Evgenii Tsymbalov Maxim Panov UQCV 41 7 0 06 Mar 2020
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks Marius Hobbhahn Agustinus Kristiadi Philipp Hennig BDL UQCV 177 34 0 02 Mar 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 90 290 0 24 Feb 2020
On the Role of Dataset Quality and Heterogeneity in Model Confidence Yuan Zhao Jiasi Chen Samet Oymak 58 14 0 23 Feb 2020
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation N. Brosse C. Riquelme Alice Martin Sylvain Gelly Eric Moulines BDL OOD UQCV 97 34 0 22 Jan 2020
Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks Oliver Willers Sebastian Sudholt Shervin Raafatnia Stephanie Abrecht 111 80 0 22 Jan 2020
Safe Robot Navigation via Multi-Modal Anomaly Detection Lorenz Wellhausen René Ranftl Marco Hutter 91 77 0 22 Jan 2020
Practical Solutions for Machine Learning Safety in Autonomous Vehicles Sina Mohseni Mandar Pitale Vasu Singh Zhangyang Wang 84 68 0 20 Dec 2019
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration Kanil Patel William H. Beluch Dan Zhang Michael Pfeiffer Bin Yang UQCV 125 30 0 16 Dec 2019
Playing it Safe: Adversarial Robustness with an Abstain Option Cassidy Laidlaw Soheil Feizi AAML 75 20 0 25 Nov 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 64 47 0 23 Oct 2019
Toward Metrics for Differentiating Out-of-Distribution Sets Mahdieh Abbasi Changjian Shui Arezoo Rajabi Christian Gagné R. Bobba OODD 39 4 0 18 Oct 2019
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks David Stutz Matthias Hein Bernt Schiele AAML 89 5 0 14 Oct 2019
Out-of-distribution Detection in Classifiers via Generation Sachin Vernekar Ashish Gaurav Vahdat Abdelzad Taylor Denouden Rick Salay Krzysztof Czarnecki OODD 112 83 0 09 Oct 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 86 141 0 26 Sep 2019
Model-Based and Data-Driven Strategies in Medical Image Computing Daniel Rueckert Julia A. Schnabel OOD MedIm AI4CE 62 50 0 23 Sep 2019
Generating Accurate Pseudo-labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations Vishnu Suresh Lokhande Songwong Tasneeyapant Abhay Venkatesh Sathya Ravi Vikas Singh 90 29 0 12 Sep 2019
Entropic Out-of-Distribution Detection David Macêdo T. I. Ren Cleber Zanchettin Adriano Oliveira Teresa B Ludermir OODD UQCV 68 33 0 15 Aug 2019
Interpretable Image Recognition with Hierarchical Prototypes Peter Hase Chaofan Chen Oscar Li Cynthia Rudin VLM 92 114 0 25 Jun 2019
Non-Parametric Calibration for Classification Jonathan Wenger Hedvig Kjellström Rudolph Triebel UQCV 120 82 0 12 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 84 62 0 08 Jun 2019
Analysis of Confident-Classifiers for Out-of-distribution Detection Sachin Vernekar Ashish Gaurav Taylor Denouden Buu Phan Vahdat Abdelzad Rick Salay Krzysztof Czarnecki OODD 61 18 0 27 Apr 2019
Exploring Uncertainty Measures for Image-Caption Embedding-and-Retrieval Task Kenta Hama Takashi Matsubara K. Uehara Jianfei Cai BDL UQCV 40 6 0 09 Apr 2019
A witness function based construction of discriminative models using Hermite polynomials H. Mhaskar A. Cloninger Xiuyuan Cheng 138 9 0 10 Jan 2019