Selective Classification for Deep Neural Networks

23 May 2017

Papers citing "Selective Classification for Deep Neural Networks"

44 / 94 papers shown

Title
Selective Classification Via Neural Network Training Dynamics Stephan Rabanser Anvith Thudi Kimia Hamidieh Adam Dziedzic Nicolas Papernot 24 21 0 26 May 2022
Offline Policy Comparison with Confidence: Benchmarks and Baselines Anurag Koul Mariano Phielipp Alan Fern OffRL 20 0 0 22 May 2022
Efficient, Uncertainty-based Moderation of Neural Networks Text Classifiers J. S. Andersen W. Maalej 14 9 0 04 Apr 2022
On the Value of ML Models Fabio Casati Pierre-Andre Noel Jie Yang 16 7 0 13 Dec 2021
Disrupting Deep Uncertainty Estimation Without Harming Accuracy Ido Galil Ran El-Yaniv AAML 13 15 0 26 Oct 2021
Evolutionary Optimization of High-Coverage Budgeted Classifiers Nolan H. Hamilton Errin W. Fulp 14 0 0 25 Oct 2021
Uncertainty-Aware Training for Cardiac Resynchronisation Therapy Response Prediction Tareen Dawood C. L. P. Chen R. Andlauer B. Sidhu B. Ruijsink ... Vishal S. Mehta C. Rinaldi Esther Puyol-Antón Reza Razavi A. King 15 2 0 22 Sep 2021
NGC: A Unified Framework for Learning with Open-World Noisy Data Zhi-Fan Wu Tong Wei Jianwen Jiang Chaojie Mao Mingqian Tang Yu-Feng Li 11 80 0 25 Aug 2021
FSNet: A Failure Detection Framework for Semantic Segmentation Q. Rahman Niko Sünderhauf Peter Corke Feras Dayoub UQCV SSeg 25 19 0 19 Aug 2021
A Survey on Open Set Recognition Atefeh Mahdavi Marco M. Carvalho BDL 19 34 0 18 Aug 2021
RISAN: Robust Instance Specific Abstention Network B. Kalra Kulin Shah Naresh Manwani 20 2 0 07 Jul 2021
Meta-Cal: Well-controlled Post-hoc Calibration by Ranking Xingchen Ma Matthew B. Blaschko 18 34 0 10 May 2021
Selective Probabilistic Classifier Based on Hypothesis Testing Saeed Bakhshi Germi Esa Rahtu H. Huttunen 22 1 0 09 May 2021
Exploring Uncertainty in Deep Learning for Construction of Prediction Intervals Yuandu Lai Yucheng Shi Yahong Han Yunfeng Shao Meiyu Qi Bingshuai Li UQCV 33 15 0 27 Apr 2021
Robust Adversarial Classification via Abstaining Abed AlRahman Al Makdah Vaibhav Katewa Fabio Pasqualetti 16 0 0 06 Apr 2021
SSD: A Unified Framework for Self-Supervised Outlier Detection Vikash Sehwag M. Chiang Prateek Mittal OODD 31 330 0 22 Mar 2021
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays E. Chen Andy Kim R. Krishnan J. Long A. Ng Pranav Rajpurkar 26 2 0 18 Mar 2021
SCRIB: Set-classifier with Class-specific Risk Bounds for Blackbox Models Zhen Lin Cao Xiao Lucas Glass M. P. M. Brandon Westover Jimeng Sun BDL 21 11 0 05 Mar 2021
Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends Q. Rahman Peter Corke Feras Dayoub OOD 27 51 0 05 Jan 2021
Achieving Adversarial Robustness Requires An Active Teacher Chao Ma Lexing Ying 19 1 0 14 Dec 2020
Confidence Estimation via Auxiliary Models Charles Corbière Nicolas Thome A. Saporta Tuan-Hung Vu Matthieu Cord P. Pérez TPM 29 47 0 11 Dec 2020
Classification with Rejection Based on Cost-sensitive Classification Nontawat Charoenphakdee Zhenghang Cui Yivan Zhang Masashi Sugiyama 68 64 0 22 Oct 2020
Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets Zhihui Shao Jianyi Yang Shaolei Ren OODD 32 11 0 16 Jun 2020
SoQal: Selective Oracle Questioning in Active Learning Dani Kiyasseh T. Zhu David A. Clifton 25 0 0 22 Apr 2020
SCOUT: Self-aware Discriminant Counterfactual Explanations Pei Wang Nuno Vasconcelos FAtt 22 81 0 16 Apr 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 24 559 0 26 Feb 2020
Adversarial Robustness for Code Pavol Bielik Martin Vechev AAML 14 89 0 11 Feb 2020
Dirichlet uncertainty wrappers for actionable algorithm accuracy accountability and auditability José Mena O. Pujol Jordi Vitrià 19 8 0 29 Dec 2019
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
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
Deep Neural Rejection against Adversarial Examples Angelo Sotgiu Ambra Demontis Marco Melis Battista Biggio Giorgio Fumera Xiaoyi Feng Fabio Roli AAML 12 68 0 01 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
Efficient Evaluation-Time Uncertainty Estimation by Improved Distillation Erik Englesson Hossein Azizpour UQCV 14 7 0 12 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 24 1,654 0 06 Jun 2019
Combating Label Noise in Deep Learning Using Abstention S. Thulasidasan Tanmoy Bhattacharya J. Bilmes Gopinath Chennupati J. Mohd-Yusof NoLa 22 177 0 27 May 2019
Recent Advances in Open Set Recognition: A Survey Chuanxing Geng Sheng-Jun Huang Songcan Chen BDL ObjD 36 756 0 21 Nov 2018
Unrestricted Adversarial Examples Tom B. Brown Nicholas Carlini Chiyuan Zhang Catherine Olsson Paul Christiano Ian Goodfellow AAML 23 101 0 22 Sep 2018
Probabilistic Binary Neural Networks Jorn W. T. Peters Max Welling BDL UQCV MQ 17 50 0 10 Sep 2018
Deep Anomaly Detection Using Geometric Transformations I. Golan Ran El-Yaniv 14 601 0 28 May 2018
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers Yonatan Geifman Guy Uziel Ran El-Yaniv UQCV 17 132 0 21 May 2018
Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes Tongfei Chen Jirí Navrátil Vijay Iyengar Karthikeyan Shanmugam 10 42 0 14 May 2018
Deep Active Learning over the Long Tail Yonatan Geifman Ran El-Yaniv 3DPC 14 143 0 02 Nov 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015