Papers citing 'Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness'

Title
Feature Space Singularity for Out-of-Distribution Detection Haiwen Huang Zhihan Li Lulu Wang Sishuo Chen Bin Dong Xinyu Zhou OODD 182 71 0 30 Nov 2020
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty Umang Bhatt Javier Antorán Yunfeng Zhang Q. V. Liao P. Sattigeri ... L. Nachman R. Chunara Madhulika Srikumar Adrian Weller Alice Xiang 179 269 0 15 Nov 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 465 2,071 0 12 Nov 2020
Hierarchical Gaussian Processes with Wasserstein-2 Kernels S. Popescu D. Sharp James H. Cole Ben Glocker 137 5 0 28 Oct 2020
Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures Benjamin Kompa Jasper Snoek Andrew L. Beam UQCV BDL 128 32 0 06 Oct 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 117 17 0 17 Aug 2020
An Uncertainty-aware Transfer Learning-based Framework for Covid-19 Diagnosis Afshar Shamsi Hamzeh Asgharnezhad Shirin Shamsi Jokandan Abbas Khosravi P. Kebria D. Nahavandi S. Nahavandi D. Srinivasan OOD 153 139 0 26 Jul 2020
Uncertainty-Aware (UNA) Bases for Deep Bayesian Regression Using Multi-Headed Auxiliary Networks Sujay Thakur Cooper Lorsung Yaniv Yacoby Finale Doshi-Velez Weiwei Pan BDL UQCV 125 4 0 21 Jun 2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors Michael W. Dusenberry Ghassen Jerfel Yeming Wen Yi-An Ma Jasper Snoek Katherine A. Heller Balaji Lakshminarayanan Dustin Tran UQCV BDL 170 221 0 14 May 2020
Uncertainty Estimation Using a Single Deep Deterministic Neural Network Joost R. van Amersfoort Lewis Smith Yee Whye Teh Y. Gal UQCV BDL 128 55 0 04 Mar 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 157 303 0 24 Feb 2020
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning Yeming Wen Dustin Tran Jimmy Ba OOD FedML UQCV 327 507 0 17 Feb 2020
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 152 143 0 26 Sep 2019
Verified Uncertainty Calibration Ananya Kumar Percy Liang Tengyu Ma 276 367 0 23 Sep 2019
Out-of-domain Detection for Natural Language Understanding in Dialog Systems Yinhe Zheng Guanyi Chen Minlie Huang 153 129 0 09 Sep 2019
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction Stefan Larson Anish Mahendran Joseph Peper Christopher Clarke Andrew Lee ... Jonathan K. Kummerfeld Kevin Leach M. Laurenzano Lingjia Tang Jason Mars 224 549 0 04 Sep 2019
Approximate Inference Turns Deep Networks into Gaussian Processes Mohammad Emtiyaz Khan Alexander Immer Ehsan Abedi M. Korzepa UQCV BDL 219 127 0 05 Jun 2019
Towards Open Intent Discovery for Conversational Text Nikhita Vedula Nedim Lipka Pranav Maneriker Srinivasan Parthasarathy 80 20 0 17 Apr 2019
A deterministic and computable Bernstein-von Mises theorem Guillaume P. Dehaene 106 15 0 04 Apr 2019
Measuring Calibration in Deep Learning Jeremy Nixon Michael W. Dusenberry Ghassen Jerfel Timothy Nguyen Jeremiah Zhe Liu Linchuan Zhang Dustin Tran UQCV 168 522 0 02 Apr 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 451 3,634 0 28 Mar 2019
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness J. Jacobsen Jens Behrmann Nicholas Carlini Florian Tramèr Nicolas Papernot AAML 93 46 0 25 Mar 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 211 751 0 28 Jan 2019
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 260 576 0 13 Dec 2018
Prior Networks for Detection of Adversarial Attacks A. Malinin Mark Gales AAML 100 5 0 06 Dec 2018
Sorting out Lipschitz function approximation Cem Anil James Lucas Roger C. Grosse 177 334 0 13 Nov 2018
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 227 646 0 02 Nov 2018
Excessive Invariance Causes Adversarial Vulnerability J. Jacobsen Jens Behrmann R. Zemel Matthias Bethge AAML 202 168 0 01 Nov 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 2.5K 98,870 0 11 Oct 2018
Challenges for Toxic Comment Classification: An In-Depth Error Analysis Betty van Aken Julian Risch Ralf Krestel Alexander Loser 86 225 0 20 Sep 2018
Noise Contrastive Priors for Functional Uncertainty Danijar Hafner Dustin Tran Timothy Lillicrap A. Irpan James Davidson AAML BDL UQCV 160 74 0 24 Jul 2018
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 347 1,090 0 05 Jun 2018
Calibrating Deep Convolutional Gaussian Processes Gia-Lac Tran Edwin V. Bonilla John P. Cunningham Pietro Michiardi Maurizio Filippone BDL UQCV 94 43 0 26 May 2018
Reachability Analysis of Deep Neural Networks with Provable Guarantees Wenjie Ruan Xiaowei Huang Marta Kwiatkowska AAML 125 271 0 06 May 2018
Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection Di Feng Lars Rosenbaum Klaus C. J. Dietmayer 3DPC UQCV 118 252 0 13 Apr 2018
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization Peter L. Bartlett S. Evans Philip M. Long 143 32 0 13 Apr 2018
Regularisation of Neural Networks by Enforcing Lipschitz Continuity Henry Gouk E. Frank Bernhard Pfahringer M. Cree 268 501 0 12 Apr 2018
Predictive Uncertainty Estimation via Prior Networks A. Malinin Mark Gales UD BDL EDL UQCV PER 317 962 0 28 Feb 2018
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling C. Riquelme George Tucker Jasper Snoek BDL 141 371 0 26 Feb 2018
i-RevNet: Deep Invertible Networks J. Jacobsen A. Smeulders Edouard Oyallon 160 340 0 20 Feb 2018
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 320 4,524 0 16 Feb 2018
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks Yusuke Tsuzuku Issei Sato Masashi Sugiyama AAML 264 319 0 12 Feb 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 137 479 0 31 Jan 2018
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples Kimin Lee Honglak Lee Kibok Lee Jinwoo Shin OODD 288 895 0 26 Nov 2017
DOC: Deep Open Classification of Text Documents Lei Shu Hu Xu Bing-Quan Liu VLM 103 304 0 25 Sep 2017
SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation Daniel Cer Mona T. Diab Eneko Agirre I. Lopez-Gazpio Lucia Specia 612 1,934 0 31 Jul 2017
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks John Bradshaw A. G. Matthews Zoubin Ghahramani BDL AAML 148 173 0 08 Jul 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 345 6,186 0 14 Jun 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 332 9,803 0 31 Mar 2017
Semi-analytical approximations to statistical moments of sigmoid and softmax mappings of normal variables J. Daunizeau 70 42 0 01 Mar 2017