Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples

26 November 2017

Papers citing "Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples"

50 / 174 papers shown

Title
InFlow: Robust outlier detection utilizing Normalizing Flows Nishant Kumar Pia Hanfeld Michael Hecht Michael Bussmann Stefan Gumhold Nico Hoffmann OODD OOD TPM 26 4 0 10 Jun 2021
Provably Robust Detection of Out-of-distribution Data (almost) for free Alexander Meinke Julian Bitterwolf Matthias Hein OODD 25 22 0 08 Jun 2021
Distribution Awareness for AI System Testing David Berend 21 8 0 06 May 2021
MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space Rui Huang Yixuan Li OODD 36 235 0 05 May 2021
MOOD: Multi-level Out-of-distribution Detection Ziqian Lin Sreya . Dutta Roy Yixuan Li OODD 26 114 0 30 Apr 2021
Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems Shohei Enomoto Takeharu Eda UQCV 46 17 0 15 Apr 2021
SSD: A Unified Framework for Self-Supervised Outlier Detection Vikash Sehwag M. Chiang Prateek Mittal OODD 31 330 0 22 Mar 2021
Posterior Meta-Replay for Continual Learning Christian Henning Maria R. Cervera Francesco DÁngelo J. Oswald Regina Traber Benjamin Ehret Seijin Kobayashi Benjamin Grewe João Sacramento CLL BDL 51 54 0 01 Mar 2021
Deep Deterministic Uncertainty: A Simple Baseline Jishnu Mukhoti Andreas Kirsch Joost R. van Amersfoort Philip H. S. Torr Y. Gal UD UQCV PER BDL 24 145 0 23 Feb 2021
Few-shot Conformal Prediction with Auxiliary Tasks Adam Fisch Tal Schuster Tommi Jaakkola Regina Barzilay 181 53 0 17 Feb 2021
Bridging In- and Out-of-distribution Samples for Their Better Discriminability Engkarat Techapanurak Anh-Chuong Dang Takayuki Okatani OODD 25 3 0 07 Jan 2021
Multidimensional Uncertainty-Aware Evidential Neural Networks Yibo Hu Yuzhe Ou Xujiang Zhao Jin-Hee Cho Feng Chen EDL UQCV AAML 25 23 0 26 Dec 2020
Task-Adaptive Negative Envision for Few-Shot Open-Set Recognition Shiyuan Huang Jiawei Ma G. Han Shih-Fu Chang BDL 33 19 0 24 Dec 2020
Entropy Maximization and Meta Classification for Out-Of-Distribution Detection in Semantic Segmentation Robin Shing Moon Chan Matthias Rottmann Hanno Gottschalk OODD 37 149 0 09 Dec 2020
The Hidden Uncertainty in a Neural Networks Activations Janis Postels Hermann Blum Yannick Strümpler Cesar Cadena Roland Siegwart Luc Van Gool Federico Tombari UQCV 30 22 0 05 Dec 2020
Feature Space Singularity for Out-of-Distribution Detection Haiwen Huang Zhihan Li Lulu Wang Sishuo Chen Bin Dong Xinyu Zhou OODD 20 65 0 30 Nov 2020
Energy-based Out-of-distribution Detection Weitang Liu Xiaoyun Wang John Douglas Owens Yixuan Li OODD 71 1,290 0 08 Oct 2020
A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning Martin Mundt Yongjun Hong Iuliia Pliushch Visvanathan Ramesh CLL 27 146 0 03 Sep 2020
On the Structures of Representation for the Robustness of Semantic Segmentation to Input Corruption Charles Lehman Dogancan Temel Ghassan AlRegib 19 4 0 02 Sep 2020
A Survey of Visual Analytics Techniques for Machine Learning Jun Yuan Changjian Chen Weikai Yang Mengchen Liu Jiazhi Xia Shixia Liu 21 216 0 21 Aug 2020
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems Zhe Chen Yuyan Wang Dong Lin D. Cheng Lichan Hong Ed H. Chi Claire Cui 28 16 0 17 Aug 2020
Multi-Task Curriculum Framework for Open-Set Semi-Supervised Learning Qing Yu Daiki Ikami Go Irie Kiyoharu Aizawa 12 128 0 22 Jul 2020
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimation Xuming Ran Mingkun Xu Lingrui Mei Qi Xu Quanying Liu OODD UQCV 39 50 0 16 Jul 2020
Contrastive Training for Improved Out-of-Distribution Detection Jim Winkens Rudy Bunel Abhijit Guha Roy Robert Stanforth Vivek Natarajan ... Alan Karthikesalingam Simon A. A. Kohl taylan. cemgil S. M. Ali Eslami Olaf Ronneberger OODD 11 234 0 10 Jul 2020
Distribution-free binary classification: prediction sets, confidence intervals and calibration Chirag Gupta A. Podkopaev Aaditya Ramdas UQCV 27 79 0 18 Jun 2020
AI Research Considerations for Human Existential Safety (ARCHES) Andrew Critch David M. Krueger 22 50 0 30 May 2020
Few-Shot Open-Set Recognition using Meta-Learning Bo Liu Hao Kang Haoxiang Li G. Hua Nuno Vasconcelos BDL EDL 20 89 0 27 May 2020
SCOUT: Self-aware Discriminant Counterfactual Explanations Pei Wang Nuno Vasconcelos FAtt 22 81 0 16 Apr 2020
Towards Inheritable Models for Open-Set Domain Adaptation Jogendra Nath Kundu Naveen Venkat R. Ambareesh V. RahulM. R. Venkatesh Babu VLM 17 117 0 09 Apr 2020
Regularizing Class-wise Predictions via Self-knowledge Distillation Sukmin Yun Jongjin Park Kimin Lee Jinwoo Shin 27 274 0 31 Mar 2020
Hybrid Models for Open Set Recognition Hongjie Zhang Ang Li Jie Guo Yanwen Guo BDL 20 184 0 27 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 75 98 0 20 Mar 2020
Anomalous Example Detection in Deep Learning: A Survey Saikiran Bulusu B. Kailkhura Bo-wen 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 329 53 0 09 Mar 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 16 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 24 558 0 26 Feb 2020
The Conditional Entropy Bottleneck Ian S. Fischer OOD 19 115 0 13 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 13 63 0 08 Feb 2020
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration Kanil Patel William H. Beluch Dan Zhang Michael Pfeiffer Bin Yang UQCV 19 30 0 16 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 24 262 0 29 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 15 455 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 33 52 0 18 Nov 2019
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning J. Liu John Paisley M. Kioumourtzoglou B. Coull UQCV UD PER 24 83 0 11 Nov 2019
Identifying Unknown Instances for Autonomous Driving K. Wong Shenlong Wang Mengye Ren Ming Liang R. Urtasun 22 110 0 24 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 19 45 0 23 Oct 2019
Out-of-distribution Detection in Classifiers via Generation Sachin Vernekar Ashish Gaurav Vahdat Abdelzad Taylor Denouden Rick Salay Krzysztof Czarnecki OODD 19 83 0 09 Oct 2019
Open Set Medical Diagnosis Viraj Prabhu A. Kannan Geoffrey Tso Namit Katariya Manish Chablani David Sontag X. Amatriain 21 9 0 07 Oct 2019
Addressing Failure Prediction by Learning Model Confidence Charles Corbière Nicolas Thome Avner Bar-Hen Matthieu Cord P. Pérez 24 281 0 01 Oct 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 22 139 0 26 Sep 2019
Out-of-domain Detection for Natural Language Understanding in Dialog Systems Yinhe Zheng Guanyi Chen Minlie Huang 18 121 0 09 Sep 2019