v1v2v3 (latest)

Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

5 December 2016

Balaji Lakshminarayanan

Alexander Pritzel

Papers citing "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles"

50 / 3,224 papers shown

Title
Generalized Learning with Rejection for Classification and Regression Problems Amina Asif F. Minhas 20 3 0 03 Nov 2019
Quantifying (Hyper) Parameter Leakage in Machine Learning Vasisht Duddu D. V. Rao AAML MIACV FedML 67 5 0 31 Oct 2019
Multivariate Uncertainty in Deep Learning Rebecca L. Russell Christopher P. Reale BDL UQCV 69 70 0 31 Oct 2019
Heteroscedastic Calibration of Uncertainty Estimators in Deep Learning Bindya Venkatesh Jayaraman J. Thiagarajan UQCV 45 6 0 30 Oct 2019
Learn-By-Calibrating: Using Calibration as a Training Objective Jayaraman J. Thiagarajan Bindya Venkatesh Deepta Rajan UQCV 53 6 0 30 Oct 2019
Generative Well-intentioned Networks J. Cosentino Jun Zhu AI4CE 37 2 0 28 Oct 2019
Towards calibrated and scalable uncertainty representations for neural networks Nabeel Seedat Christopher Kanan UQCV 77 19 0 28 Oct 2019
Thieves on Sesame Street! Model Extraction of BERT-based APIs Kalpesh Krishna Gaurav Singh Tomar Ankur P. Parikh Nicolas Papernot Mohit Iyyer MIACV MLAU 142 201 0 27 Oct 2019
CXPlain: Causal Explanations for Model Interpretation under Uncertainty Patrick Schwab W. Karlen FAtt CML 122 211 0 27 Oct 2019
Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians Axel Brando Jose A. Rodríguez-Serrano Jordi Vitrià Alberto Rubio 60 22 0 27 Oct 2019
Federated Uncertainty-Aware Learning for Distributed Hospital EHR Data Sabri Boughorbel Fethi Jarray Neethu Venugopal S. Moosa Haithum Elhadi Michel Makhlouf OOD FedML 131 53 0 27 Oct 2019
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search Colin White Willie Neiswanger Yash Savani BDL 126 329 0 25 Oct 2019
Accurate Layerwise Interpretable Competence Estimation Vickram Rajendran Will LeVine 82 10 0 24 Oct 2019
We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric Uncertainty T. LaBonte Carianne Martinez S. Roberts UQCV 3DV 53 31 0 23 Oct 2019
Stabilising priors for robust Bayesian deep learning Felix Mcgregor Arnu Pretorius J. D. Preez Steve Kroon BDL UQCV 28 3 0 23 Oct 2019
Deep Learning at the Edge Sahar Voghoei N. Tonekaboni Jason G. Wallace H. Arabnia 175 41 0 22 Oct 2019
Robust Training with Ensemble Consensus Jisoo Lee Sae-Young Chung NoLa 81 28 0 22 Oct 2019
Detecting Underspecification with Local Ensembles David Madras James Atwood Alexander DÁmour 64 4 0 21 Oct 2019
Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods Eyke Hüllermeier Willem Waegeman PER UD 268 1,440 0 21 Oct 2019
Unsupervised Out-of-Distribution Detection with Batch Normalization Jiaming Song Yang Song Stefano Ermon OODD 69 22 0 21 Oct 2019
Toward Metrics for Differentiating Out-of-Distribution Sets Mahdieh Abbasi Changjian Shui Arezoo Rajabi Christian Gagné R. Bobba OODD 30 4 0 18 Oct 2019
Deep Sub-Ensembles for Fast Uncertainty Estimation in Image Classification Matias Valdenegro-Toro UQCV 113 52 0 17 Oct 2019
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost M. Gao Zizhao Zhang Guo-Ding Yu Sercan O. Arik L. Davis Tomas Pfister 236 200 0 16 Oct 2019
Deep Kernels with Probabilistic Embeddings for Small-Data Learning Ankur Mallick Chaitanya Dwivedi B. Kailkhura Gauri Joshi T. Y. Han BDL UQCV 44 8 0 13 Oct 2019
Information Aware Max-Norm Dirichlet Networks for Predictive Uncertainty Estimation Theodoros Tsiligkaridis UQCV BDL 46 8 0 10 Oct 2019
NGBoost: Natural Gradient Boosting for Probabilistic Prediction Tony Duan Anand Avati D. Ding Khanh K. Thai S. Basu A. Ng Alejandro Schuler BDL 67 306 0 08 Oct 2019
Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction Gabriele Scalia Colin A. Grambow Barbara Pernici Yi‐Pei Li W. Green BDL 89 8 0 07 Oct 2019
Open Set Medical Diagnosis Viraj Prabhu A. Kannan Geoffrey Tso Namit Katariya Manish Chablani David Sontag X. Amatriain 49 9 0 07 Oct 2019
Deep Evidential Regression Alexander Amini Wilko Schwarting A. Soleimany Daniela Rus EDL PER BDL UD UQCV 120 444 0 07 Oct 2019
Requirements for Developing Robust Neural Networks Rulin Shao Michael Lee VLM 34 1 0 04 Oct 2019
Revisiting Classical Bagging with Modern Transfer Learning for On-the-fly Disaster Damage Detector Jiaxing Huang Seungwon Lee Jingyi Zhang Taegyun Jeon 49 6 0 04 Oct 2019
Predicting materials properties without crystal structure: Deep representation learning from stoichiometry Rhys E. A. Goodall A. Lee 81 262 0 01 Oct 2019
Addressing Failure Prediction by Learning Model Confidence Charles Corbière Nicolas Thome Avner Bar-Hen Matthieu Cord P. Pérez 124 292 0 01 Oct 2019
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate Lu Mi Hao Wang Yonglong Tian Hao He Nir Shavit UQCV 62 32 0 28 Sep 2019
Energy-Based Models for Deep Probabilistic Regression Fredrik K. Gustafsson Martin Danelljan Goutam Bhat Thomas B. Schon UQCV BDL 74 4 0 26 Sep 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 81 141 0 26 Sep 2019
Regularising Deep Networks with Deep Generative Models M. Willetts A. Camuto Stephen J. Roberts Chris Holmes UQCV 22 0 0 25 Sep 2019
Input complexity and out-of-distribution detection with likelihood-based generative models Joan Serrà David Álvarez Vicencc Gómez Olga Slizovskaia José F. Núñez Jordi Luque OODD 166 277 0 25 Sep 2019
Residual Reactive Navigation: Combining Classical and Learned Navigation Strategies For Deployment in Unknown Environments Krishan Rana Ben Talbot Vibhavari Dasagi Michael Milford Niko Sünderhauf 90 22 0 24 Sep 2019
Sampling Bias in Deep Active Classification: An Empirical Study Ameya Prabhu Charles Dognin M. Singh 78 64 0 20 Sep 2019
Evaluating and Boosting Uncertainty Quantification in Classification Xiaoyang Huang Jiancheng Yang Linguo Li Haoran Deng Bingbing Ni Yi Tian Xu 40 9 0 13 Sep 2019
Probabilistic framework for solving Visual Dialog Badri N. Patro Anupriy Vinay P. Namboodiri BDL 141 13 0 11 Sep 2019
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors Jayaraman J. Thiagarajan Bindya Venkatesh P. Sattigeri P. Bremer UQCV 63 31 0 09 Sep 2019
High Accuracy and High Fidelity Extraction of Neural Networks Matthew Jagielski Nicholas Carlini David Berthelot Alexey Kurakin Nicolas Papernot MLAU MIACV 99 382 0 03 Sep 2019
Urban flows prediction from spatial-temporal data using machine learning: A survey Peng Xie Tianrui Li Jia Liu Shengdong Du Xin Yang Junbo Zhang AI4TS AI4CE 72 74 0 26 Aug 2019
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels Felix J. S. Bragman Ryutaro Tanno Sebastien Ourselin Daniel C. Alexander M. Jorge Cardoso 73 87 0 26 Aug 2019
Marginally-calibrated deep distributional regression Nadja Klein David J. Nott M. Smith UQCV 86 14 0 26 Aug 2019
Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural Networks Juan Maroñas Roberto Paredes Palacios D. Ramos-Castro UQCV BDL 102 24 0 23 Aug 2019
Adversarial-Based Knowledge Distillation for Multi-Model Ensemble and Noisy Data Refinement Zhiqiang Shen Zhankui He Wanyun Cui Jiahui Yu Yutong Zheng Chenchen Zhu Marios Savvides AAML 36 5 0 22 Aug 2019
n-MeRCI: A new Metric to Evaluate the Correlation Between Predictive Uncertainty and True Error Michel Moukari Loïc Simon Sylvaine Picard F. Jurie UQCV 57 4 0 20 Aug 2019