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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
A Large-Scale Study of Probabilistic Calibration in Neural Network Regression Victor Dheur Souhaib Ben Taieb BDL 194 14 0 05 Jun 2023
Towards Anytime Classification in Early-Exit Architectures by Enforcing Conditional Monotonicity Metod Jazbec J. Allingham Dan Zhang Eric T. Nalisnick 63 11 0 05 Jun 2023
Uncertainty in Natural Language Processing: Sources, Quantification, and Applications Mengting Hu Zhen Zhang Shiwan Zhao Minlie Huang Bingzhe Wu BDL 103 39 0 05 Jun 2023
Sen2Pro: A Probabilistic Perspective to Sentence Embedding from Pre-trained Language Model Lingfeng Shen Haiyun Jiang Lemao Liu Shuming Shi 64 2 0 04 Jun 2023
Provable Dynamic Fusion for Low-Quality Multimodal Data Qingyang Zhang Haitao Wu Changqing Zhang Qinghua Hu Huazhu Fu Qiufeng Wang Xi Peng 118 62 0 03 Jun 2023
A Data-Driven Measure of Relative Uncertainty for Misclassification Detection Eduardo Dadalto Camara Gomes Marco Romanelli Georg Pichler Pablo Piantanida UQCV 95 5 0 02 Jun 2023
Calibrating Multimodal Learning Huanrong Zhang Changqing Zhang Bing Wu Huazhu Fu Qiufeng Wang Q. Hu 100 21 0 02 Jun 2023
A General Framework for Uncertainty Quantification via Neural SDE-RNN Shweta Dahale Sai Munikoti Balasubramaniam Natarajan AI4TS UQCV BDL 51 1 0 01 Jun 2023
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding Alizée Pace Hugo Yèche Bernhard Schölkopf Gunnar Rätsch Guy Tennenholtz OffRL 67 7 0 01 Jun 2023
Improving day-ahead Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context Oussama Boussif Ghait Boukachab D. Assouline Stefano Massaroli T. Yuan L. Benabbou Yoshua Bengio 79 16 0 01 Jun 2023
Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization Navid Ansari Hans-Peter Seidel Vahid Babaei 77 2 0 01 Jun 2023
Quantifying Deep Learning Model Uncertainty in Conformal Prediction Hamed Karimi Reza Samavi UQCV 76 11 0 01 Jun 2023
On the Limitations of Temperature Scaling for Distributions with Overlaps Muthuraman Chidambaram Rong Ge UQCV 91 4 0 01 Jun 2023
Hinge-Wasserstein: Estimating Multimodal Aleatoric Uncertainty in Regression Tasks Ziliang Xiong Arvi Jonnarth Abdelrahman Eldesokey Joakim Johnander Bastian Wandt Per-Erik Forssén UQCV 85 3 0 01 Jun 2023
Quantifying Representation Reliability in Self-Supervised Learning Models Young-Jin Park Hao Wang Shervin Ardeshir Navid Azizan SSL UQCV 95 5 0 31 May 2023
Probabilistic Uncertainty Quantification of Prediction Models with Application to Visual Localization Junan Chen Josephine Monica Wei-Lun Chao Mark E. Campbell 67 5 0 31 May 2023
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization Y. Li Tim G. J. Rudner A. Wilson BDL 99 34 0 31 May 2023
A Bayesian Approach To Analysing Training Data Attribution In Deep Learning Elisa Nguyen Minjoon Seo Seong Joon Oh BDL 621 8 0 31 May 2023
DiffLoad: Uncertainty Quantification in Load Forecasting with Diffusion Model Zhixian Wang Qingsong Wen Chaoli Zhang Liang Sun Yi Wang DiffM 75 5 0 31 May 2023
Perception and Semantic Aware Regularization for Sequential Confidence Calibration Zhenghua Peng Yuanmao Luo Tianshui Chen Keke Xu Shuangping Huang AI4TS 85 2 0 31 May 2023
infoVerse: A Universal Framework for Dataset Characterization with Multidimensional Meta-information Jaehyung Kim Yekyung Kim Karin de Langis Jinwoo Shin Dongyeop Kang 59 1 0 30 May 2023
Probabilistic computation and uncertainty quantification with emerging covariance He Ma Yong Qi Li Zhang Wenlian Lu Jianfeng Feng 51 1 0 30 May 2023
Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models Zhen Lin Shubhendu Trivedi Jimeng Sun HILM 214 157 0 30 May 2023
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks Yuwen Li Miao Xiong Bryan Hooi 86 7 0 30 May 2023
Elongated Physiological Structure Segmentation via Spatial and Scale Uncertainty-aware Network Yinglin Zhang Ruiling Xi Huazhu Fu D. Towey Ruibin Bai Risa Higashita Jiang-Dong Liu 69 2 0 30 May 2023
When Does Optimizing a Proper Loss Yield Calibration? Jarosław Błasiok Parikshit Gopalan Lunjia Hu Preetum Nakkiran 100 28 0 30 May 2023
Perturbation-Assisted Sample Synthesis: A Novel Approach for Uncertainty Quantification Yifei Liu Rex Shen Xiaotong Shen DiffM 75 1 0 30 May 2023
Parity Calibration Youngseog Chung Aaron M. Rumack Chirag Gupta 85 2 0 29 May 2023
Generalized equivalences between subsampling and ridge regularization Pratik V. Patil Jin-Hong Du 97 5 0 29 May 2023
Feature-Learning Networks Are Consistent Across Widths At Realistic Scales Nikhil Vyas Alexander B. Atanasov Blake Bordelon Depen Morwani Sabarish Sainathan Cengiz Pehlevan 131 26 0 28 May 2023
Training Private Models That Know What They Don't Know Stephan Rabanser Anvith Thudi Abhradeep Thakurta Krishnamurthy Dvijotham Nicolas Papernot 87 7 0 28 May 2023
USIM-DAL: Uncertainty-aware Statistical Image Modeling-based Dense Active Learning for Super-resolution Vikrant Rangnekar Uddeshya Upadhyay Zeynep Akata Biplab Banerjee 74 4 0 27 May 2023
Maskomaly:Zero-Shot Mask Anomaly Segmentation J. Ackermann Daniel Gehrig Feng Yu ISeg 126 25 0 26 May 2023
Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection Marc Lafon Elias Ramzi Clément Rambour Nicolas Thome OODD 133 10 0 26 May 2023
Improving Neural Additive Models with Bayesian Principles Kouroche Bouchiat Alexander Immer Hugo Yèche Gunnar Rätsch Vincent Fortuin BDL MedIm 110 6 0 26 May 2023
Pedestrian Trajectory Forecasting Using Deep Ensembles Under Sensing Uncertainty Anshul Nayak A. Eskandarian Zachary R. Doerzaph P. Ghorai 70 7 0 26 May 2023
Efficient Detection of LLM-generated Texts with a Bayesian Surrogate Model Yibo Miao Hongcheng Gao Hao Zhang Zhijie Deng DeLMO 84 20 0 26 May 2023
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks Felix Jimenez Matthias Katzfuss BDL UQCV 111 1 0 26 May 2023
UMat: Uncertainty-Aware Single Image High Resolution Material Capture Carlos Rodriguez-Pardo Henar Dominguez-Elvira David Pascual-Hernández Elena Garces 77 16 0 25 May 2023
Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting Hilaf Hasson Danielle C. Maddix Yuyang Wang Gaurav Gupta Youngsuk Park UQCV AI4TS FedML 54 3 0 25 May 2023
How to Fix a Broken Confidence Estimator: Evaluating Post-hoc Methods for Selective Classification with Deep Neural Networks L. F. P. Cattelan Danilo Silva UQCV 130 6 0 24 May 2023
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods Veit Wild Sahra Ghalebikesabi Dino Sejdinovic Jeremias Knoblauch BDL UQCV 98 16 0 24 May 2023
Sampling-based Uncertainty Estimation for an Instance Segmentation Network Florian Heidecker A. El-khateeb Bernhard Sick UQCV 70 1 0 24 May 2023
Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning Moonseok Choi Hyungi Lee G. Nam Juho Lee 78 2 0 24 May 2023
Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference Insung Kong Dongyoon Yang Jongjin Lee Ilsang Ohn Gyuseung Baek Yongdai Kim BDL 86 5 0 24 May 2023
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks Kexin Huang Ying Jin Emmanuel Candès J. Leskovec 268 63 0 23 May 2023
Gaussian Latent Representations for Uncertainty Estimation using Mahalanobis Distance in Deep Classifiers A. Venkataramanan Assia Benbihi Martin Laviale C´edric Pradalier UQCV 82 10 0 23 May 2023
UPNet: Uncertainty-based Picking Deep Learning Network for Robust First Break Picking Hongtao Wang Jiangshe Zhang Xiaoli Wei Lihong Long Chunxia Zhang OOD 58 2 0 23 May 2023
Dual Focal Loss for Calibration Linwei Tao Minjing Dong Chang Xu UQCV 91 30 0 23 May 2023
Bayesian Numerical Integration with Neural Networks Katharina Ott Michael Tiemann Philipp Hennig F. Briol BDL 72 3 0 22 May 2023