Robust uncertainty estimates with out-of-distribution pseudo-inputs
training

Robust uncertainty estimates with out-of-distribution pseudo-inputs training

15 January 2022

Yevgen Zainchkovskyy

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Papers citing "Robust uncertainty estimates with out-of-distribution pseudo-inputs training"

18 / 18 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 112 312 0 24 Sep 2020
Variational Variance: Simple, Reliable, Calibrated Heteroscedastic Noise Variance Parameterization Andrew Stirn David A. Knowles DRL 64 10 0 08 Jun 2020
Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles Siddhartha Jain Ge Liu Jonas W. Mueller David K Gifford UQCV 59 60 0 18 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 170 1,704 0 06 Jun 2019
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 183 1,483 0 11 Dec 2018
Predictive Uncertainty Estimation via Prior Networks A. Malinin Mark Gales UD BDL EDL UQCV PER 193 922 0 28 Feb 2018
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples Kimin Lee Honglak Lee Kibok Lee Jinwoo Shin OODD 118 882 0 26 Nov 2017
Latent Space Oddity: on the Curvature of Deep Generative Models Georgios Arvanitidis Lars Kai Hansen Søren Hauberg DRL 107 270 0 31 Oct 2017
Good Semi-supervised Learning that Requires a Bad GAN Zihang Dai Zhilin Yang Fan Yang William W. Cohen Ruslan Salakhutdinov GAN 55 483 0 27 May 2017
Learning from Simulated and Unsupervised Images through Adversarial Training A. Shrivastava Tomas Pfister Oncel Tuzel J. Susskind Wenda Wang Russ Webb GAN 103 1,801 0 22 Dec 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 166 3,468 0 07 Oct 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 287 4,807 0 04 Jan 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 831 9,345 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 192 1,892 0 20 May 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 130 946 0 18 Feb 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 280 19,107 0 20 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 169 3,275 0 05 Dec 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 452 16,929 0 20 Dec 2013

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