Papers citing 'On Calibration of Modern Neural Networks'

Title
Evaluating Bayesian Deep Learning Methods for Semantic Segmentation Jishnu Mukhoti Y. Gal UQCV BDL 221 244 0 30 Nov 2018
Deep learning for pedestrians: backpropagation in CNNs L. Boué 3DV PINN 105 6 0 29 Nov 2018
Calibrating Uncertainties in Object Localization Task Buu Phan Rick Salay Krzysztof Czarnecki Vahdat Abdelzad Taylor Denouden Sachin Vernekar UQCV 137 24 0 27 Nov 2018
Label-Noise Robust Generative Adversarial Networks Takuhiro Kaneko Yoshitaka Ushiku Tatsuya Harada NoLa 227 68 0 27 Nov 2018
Probabilistic Object Detection: Definition and Evaluation David Hall Feras Dayoub John Skinner Haoyang Zhang Dimity Miller Peter Corke G. Carneiro A. Angelova Niko Sünderhauf UQCV 177 116 0 27 Nov 2018
Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation for Structure-wise Quality ControlNeuroImage (NeuroImage), 2018 Abhijit Guha Roy Sailesh Conjeti Nassir Navab Christian Wachinger UQCV 118 130 0 24 Nov 2018
Seeing in the dark with recurrent convolutional neural networks Till S. Hartmann 63 4 0 21 Nov 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 296 511 0 19 Nov 2018
Learning to Compensate Photovoltaic Power Fluctuations from Images of the Sky by Imitating an Optimal Policy R. Spiess Felix Berkenkamp J. Poland Andreas Krause 54 1 0 13 Nov 2018
Co-Representation Learning For Classification and Novel Class Detection via Deep Networks Zhuoyi Wang Zelun Kong Hemeng Tao Swarup Chandra Latifur Khan 56 2 0 13 Nov 2018
Large-Scale Visual Active Learning with Deep Probabilistic Ensembles Kashyap Chitta J. Álvarez Adam Lesnikowski BDL UQCV 219 37 0 08 Nov 2018
Active Learning using Deep Bayesian Networks for Surgical Workflow AnalysisInternational Journal of Computer Assisted Radiology and Surgery (IJCARS), 2018 S. Bodenstedt Dominik Rivoir L. Mündermann M. Wagner Michael Breucha Beat Müller-Stich S. T. Mees Jürgen Weitz Stefanie Speidel 139 48 0 08 Nov 2018
Deep Weighted Averaging Classifiers Dallas Card Michael J.Q. Zhang Hao Tang 192 42 0 06 Nov 2018
Single-Model Uncertainties for Deep Learning Natasa Tagasovska David Lopez-Paz UQCV BDL 530 26 0 02 Nov 2018
Understanding Deep Neural Networks through Input Uncertainties Jayaraman J. Thiagarajan Irene Kim Rushil Anirudh P. Bremer UQCV AAML 164 14 0 31 Oct 2018
Attended Temperature Scaling: A Practical Approach for Calibrating Deep Neural Networks A. Mozafari H. Gomes Wilson Leão Steeven Janny Christian Gagné 212 32 0 27 Oct 2018
Scalable Gaussian Processes on Discrete Domains Vincent Fortuin Gideon Dresdner Heiko Strathmann Gunnar Rätsch BDL 169 4 0 24 Oct 2018
What can AI do for me: Evaluating Machine Learning Interpretations in Cooperative Play Shi Feng Jordan L. Boyd-Graber HAI 252 138 0 23 Oct 2018
Good Initializations of Variational Bayes for Deep Models Simone Rossi Pietro Michiardi Maurizio Filippone BDL 231 23 0 18 Oct 2018
Shallow-Deep Networks: Understanding and Mitigating Network Overthinking Yigitcan Kaya Sanghyun Hong Tudor Dumitras 69 5 0 16 Oct 2018
Taming the Cross Entropy Loss Manuel Martínez Rainer Stiefelhagen NoLa 96 52 0 11 Oct 2018
Complementary-Label Learning for Arbitrary Losses and Models Takashi Ishida Gang Niu A. Menon Masashi Sugiyama VLM 274 123 0 10 Oct 2018
Rate Distortion For Model Compression: From Theory To Practice Weihao Gao Yu-Han Liu Chong-Jun Wang Sewoong Oh 160 35 0 09 Oct 2018
Design by adaptive sampling David H. Brookes Jennifer Listgarten TPM 198 70 0 08 Oct 2018
Inhibited Softmax for Uncertainty Estimation in Neural Networks Marcin Mo.zejko Mateusz Susik Rafal Karczewski UQCV 151 35 0 03 Oct 2018
Learning for Single-Shot Confidence Calibration in Deep Neural Networks through Stochastic InferencesComputer Vision and Pattern Recognition (CVPR), 2018 Seonguk Seo Paul Hongsuck Seo Bohyung Han FedML UQCV BDL 380 79 0 28 Sep 2018
Dropout Distillation for Efficiently Estimating Model Confidence Corina Gurau Alex Bewley Ingmar Posner BDL UQCV 90 21 0 27 Sep 2018
Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Errors for Deep Neural NetworksJournal of Chemical Information and Modeling (JCIM), 2018 I. Cortés-Ciriano A. Bender OOD UQCV 126 62 0 24 Sep 2018
Unrestricted Adversarial Examples Tom B. Brown Nicholas Carlini Chiyuan Zhang Catherine Olsson Paul Christiano Ian Goodfellow AAML 142 106 0 22 Sep 2018
Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection Dimity Miller Feras Dayoub Michael Milford Niko Sünderhauf 218 113 0 17 Sep 2018
Maximum-Entropy Fine-Grained Classification Abhimanyu Dubey O. Gupta Ramesh Raskar Nikhil Naik 170 163 0 16 Sep 2018
A Less Biased Evaluation of Out-of-distribution Sample Detectors Alireza Shafaei Mark Schmidt James J. Little OODD 223 59 0 13 Sep 2018
Heated-Up Softmax Embedding Xu-Yao Zhang Felix X. Yu Svebor Karaman Wei Zhang Shih-Fu Chang 104 47 0 11 Sep 2018
Interpreting Neural Networks With Nearest Neighbors Eric Wallace Shi Feng Jordan L. Boyd-Graber AAML FAtt MILM 263 56 0 08 Sep 2018
On the Calibration of Nested Dichotomies for Large Multiclass Tasks Tim Leathart E. Frank Bernhard Pfahringer G. Holmes 98 1 0 08 Sep 2018
Task adapted reconstruction for inverse problems J. Adler Sebastian Lunz Olivier Verdier Carola-Bibiane Schönlieb Ozan Oktem 141 48 0 27 Aug 2018
ParaNet - Using Dense Blocks for Early Inference Jo Chuang Eric Tsai Kevin Huang Jay Fetter PINN 28 1 0 24 Aug 2018
Discriminative out-of-distribution detection for semantic segmentation Petra Bevandić Ivan Kreso Marin Orsic Sinisa Segvic 168 86 0 23 Aug 2018
Improving Simple Models with Confidence ProfilesNeural Information Processing Systems (NeurIPS), 2018 Amit Dhurandhar Karthikeyan Shanmugam Ronny Luss Peder Olsen 144 47 0 19 Jul 2018
Zap: Making Predictions Based on Online User Behavior Yuri Chervonyi Dragos Harabor Brian Zhang Josh Sacks VLM 44 0 0 16 Jul 2018
Direct Uncertainty Prediction for Medical Second OpinionsInternational Conference on Machine Learning (ICML), 2018 M. Raghu Katy Blumer Rory Sayres Ziad Obermeyer Robert D. Kleinberg S. Mullainathan Jon M. Kleinberg OOD UD 369 143 0 04 Jul 2018
Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters Aniruddh Raghu Omer Gottesman Yao Liu Matthieu Komorowski A. Faisal Finale Doshi-Velez Emma Brunskill OffRL 153 36 0 03 Jul 2018
Uncertainty in the Variational Information Bottleneck Alexander A. Alemi Ian S. Fischer Joshua V. Dillon 236 106 0 02 Jul 2018
Accurate Uncertainties for Deep Learning Using Calibrated RegressionInternational Conference on Machine Learning (ICML), 2018 Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 484 725 0 01 Jul 2018
A New Angle on L2 Regularization T. Tanay Lewis D. Griffin LLMSV 108 5 0 28 Jun 2018
Adversarial Distillation of Bayesian Neural Network PosteriorsInternational Conference on Machine Learning (ICML), 2018 Kuan-Chieh Wang Paul Vicol James Lucas Li Gu Roger C. Grosse R. Zemel UQCV GAN AAML BDL 144 58 0 27 Jun 2018
xGEMs: Generating Examplars to Explain Black-Box Models Shalmali Joshi Oluwasanmi Koyejo Been Kim Joydeep Ghosh MLAU 136 41 0 22 Jun 2018
Countdown Regression: Sharp and Calibrated Survival Predictions Anand Avati Tony Duan Sharon Zhou Kenneth Jung N. Shah A. Ng 436 60 0 21 Jun 2018
Built-in Vulnerabilities to Imperceptible Adversarial Perturbations T. Tanay Jerone T. A. Andrews Lewis D. Griffin 136 7 0 19 Jun 2018
Impostor Networks for Fast Fine-Grained Recognition V. Lebedev Artem Babenko Victor Lempitsky 105 3 0 13 Jun 2018