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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"

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Title
Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning Matej Jusup Barna Pásztor Tadeusz Janik Kecheng Zhang Francesco Corman Andreas Krause Ilija Bogunovic 83 3 0 29 Jun 2023
Integrating Large Pre-trained Models into Multimodal Named Entity Recognition with Evidential Fusion Weide Liu Xiaoyang Zhong Jingwen Hou Shaohua Li Haozhe Huang Yuming Fang EDL 56 5 0 29 Jun 2023
PCDAL: A Perturbation Consistency-Driven Active Learning Approach for Medical Image Segmentation and Classification Tao Wang Xinlin Zhang Yuanbo Zhou Junlin Lan T. Tan Min Du Qinquan Gao Tong Tong 59 0 0 29 Jun 2023
Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging Max Zimmer Christoph Spiegel Sebastian Pokutta MoMe 131 14 0 29 Jun 2023
Understanding Pathologies of Deep Heteroskedastic Regression Eliot Wong-Toi Alex Boyd Vincent Fortuin Stephan Mandt UQCV 69 3 0 29 Jun 2023
Introspective Perception for Mobile Robots Sadegh Rabiee Joydeep Biswas 77 4 0 29 Jun 2023
Scalable Neural Contextual Bandit for Recommender Systems Zheqing Zhu Benjamin Van Roy OffRL 88 9 0 26 Jun 2023
Beyond AUROC & co. for evaluating out-of-distribution detection performance Galadrielle Humblot-Renaux Sergio Escalera T. Moeslund OODD 78 5 0 26 Jun 2023
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs Miao Xiong Zhiyuan Hu Xinyang Lu Yifei Li Jie Fu Junxian He Bryan Hooi 241 452 0 22 Jun 2023
Finite-time Lyapunov exponents of deep neural networks L. Storm Hampus Linander J. Bec K. Gustavsson Bernhard Mehlig 49 6 0 21 Jun 2023
Optimistic Active Exploration of Dynamical Systems Bhavya Sukhija Lenart Treven Cansu Sancaktar Sebastian Blaes Stelian Coros Andreas Krause 124 18 0 21 Jun 2023
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift Florian Seligmann P. Becker Michael Volpp Gerhard Neumann UQCV 87 16 0 21 Jun 2023
Uncertainty Estimation for Molecules: Desiderata and Methods Tom Wollschlager Nicholas Gao Bertrand Charpentier Mohamed Amine Ketata Stephan Günnemann 93 10 0 20 Jun 2023
Traversing Between Modes in Function Space for Fast Ensembling Eunggu Yun Hyungi Lee G. Nam Juho Lee UQCV 69 3 0 20 Jun 2023
Hyperbolic Active Learning for Semantic Segmentation under Domain Shift Luca Franco Paolo Mandica Konstantinos Kallidromitis Devin Guillory Yu-Teng Li Trevor Darrell Fabio Galasso 133 10 0 19 Jun 2023
Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts Annie S. Chen Yoonho Lee Amrith Rajagopal Setlur Sergey Levine Chelsea Finn OOD 106 5 0 19 Jun 2023
Learn to Accumulate Evidence from All Training Samples: Theory and Practice Deepshikha Pandey Qi Yu EDL 74 18 0 19 Jun 2023
Multi-view 3D Object Reconstruction and Uncertainty Modelling with Neural Shape Prior Ziwei Liao Steven L. Waslander 114 8 0 17 Jun 2023
Spatial-SpinDrop: Spatial Dropout-based Binary Bayesian Neural Network with Spintronics Implementation Soyed Tuhin Ahmed K. Danouchi Michael Hefenbrock G. Prenat L. Anghel M. Tahoori 68 8 0 16 Jun 2023
Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding Myrl G. Marmarelis Greg Ver Steeg Aram Galstyan Fred Morstatter CML OOD 102 5 0 15 Jun 2023
Improving Selective Visual Question Answering by Learning from Your Peers Corentin Dancette Spencer Whitehead Rishabh Maheshwary Ramakrishna Vedantam Stefan Scherer Xinlei Chen Matthieu Cord Marcus Rohrbach AAML OOD 89 17 0 14 Jun 2023
Integrating Uncertainty Awareness into Conformalized Quantile Regression Raphael Rossellini Rina Foygel Barber Rebecca Willett 195 10 0 14 Jun 2023
MUBen: Benchmarking the Uncertainty of Molecular Representation Models Yinghao Li Lingkai Kong Yuanqi Du Yue Yu Yuchen Zhuang Wenhao Mu Chao Zhang 101 11 0 14 Jun 2023
Distribution Shift Inversion for Out-of-Distribution Prediction Runpeng Yu Songhua Liu Xingyi Yang Xinchao Wang OODD 100 19 0 14 Jun 2023
Multiclass Confidence and Localization Calibration for Object Detection Bimsara Pathiraja Malitha Gunawardhana M. H. Khan UQCV 97 15 0 14 Jun 2023
Lookaround Optimizer: $k$ steps around, 1 step average Jiangtao Zhang Shunyu Liu Mingli Song Tongtian Zhu Zhenxing Xu Mingli Song MoMe 116 6 0 13 Jun 2023
Deep Gaussian Mixture Ensembles Yousef El-Laham Niccolò Dalmasso Elizabeth Fons Svitlana Vyetrenko BDL UQCV 62 2 0 12 Jun 2023
Riemannian Laplace approximations for Bayesian neural networks Federico Bergamin Pablo Moreno-Muñoz Søren Hauberg Georgios Arvanitidis BDL 81 7 0 12 Jun 2023
Mitigating Transformer Overconfidence via Lipschitz Regularization Wenqian Ye Yunsheng Ma Xu Cao Kun Tang 72 13 0 12 Jun 2023
Diverse Projection Ensembles for Distributional Reinforcement Learning Moritz A. Zanger Wendelin Bohmer M. Spaan 57 6 0 12 Jun 2023
Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing Ziyan Wang Hao Wang UQCV 82 0 0 11 Jun 2023
Push: Concurrent Probabilistic Programming for Bayesian Deep Learning Daniel Huang Christian Camaño Jonathan Tsegaye Jonathan Austin Gale AI4CE 84 0 0 10 Jun 2023
How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations Franck Djeumou Cyrus Neary Ufuk Topcu DiffM 86 10 0 10 Jun 2023
Conformalizing Machine Translation Evaluation Chrysoula Zerva André F.T. Martins 145 3 0 09 Jun 2023
Consistent Explanations in the Face of Model Indeterminacy via Ensembling Dan Ley Leonard Tang Matthew Nazari Hongjin Lin Suraj Srinivas Himabindu Lakkaraju 73 2 0 09 Jun 2023
Explaining Predictive Uncertainty with Information Theoretic Shapley Values David S. Watson Joshua O'Hara Niek Tax Richard Mudd Ido Guy TDI FAtt 70 24 0 09 Jun 2023
Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks Ziyi Huang Henry Lam Haofeng Zhang UQCV 84 7 0 09 Jun 2023
Topology-Aware Uncertainty for Image Segmentation Saumya Gupta Yikai Zhang Xiaoling Hu Prateek Prasanna Chao Chen 82 30 0 09 Jun 2023
On the Importance of Exploration for Generalization in Reinforcement Learning Yiding Jiang J. Zico Kolter Roberta Raileanu UQCV OffRL 80 24 0 08 Jun 2023
CUED at ProbSum 2023: Hierarchical Ensemble of Summarization Models Potsawee Manakul Yassir Fathullah Adian Liusie Vyas Raina Vatsal Raina Mark Gales 65 12 0 08 Jun 2023
Population-Based Evolutionary Gaming for Unsupervised Person Re-identification Yunpeng Zhai Peixi Peng Mengxi Jia Shiyong Li Weiqiang Chen Xuesong Gao Yonghong Tian 81 14 0 08 Jun 2023
Beyond Probability Partitions: Calibrating Neural Networks with Semantic Aware Grouping Jia-Qi Yang De-Chuan Zhan Le Gan UQCV 65 5 0 08 Jun 2023
Conservative Prediction via Data-Driven Confidence Minimization Caroline Choi Fahim Tajwar Yoonho Lee Huaxiu Yao Ananya Kumar Chelsea Finn 73 5 0 08 Jun 2023
On the Joint Interaction of Models, Data, and Features Yiding Jiang Christina Baek J. Zico Kolter FedML 62 4 0 07 Jun 2023
Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards Alexandre Ramé Guillaume Couairon Mustafa Shukor Corentin Dancette Jean-Baptiste Gaya Laure Soulier Matthieu Cord MoMe 123 158 0 07 Jun 2023
Optimal Transport Model Distributional Robustness Van-Anh Nguyen Trung Le Anh Tuan Bui Thanh-Toan Do Dinh Q. Phung OOD 85 4 0 07 Jun 2023
Exploring Simple, High Quality Out-of-Distribution Detection with L2 Normalization J. Haas William Yolland B. Rabus OODD 62 2 0 07 Jun 2023
CUE: An Uncertainty Interpretation Framework for Text Classifiers Built on Pre-Trained Language Models Jiazheng Li ZHAOYUE SUN Bin Liang Lin Gui Yulan He 79 2 0 06 Jun 2023
Early Weight Averaging meets High Learning Rates for LLM Pre-training Sunny Sanyal A. Neerkaje Jean Kaddour Abhishek Kumar Sujay Sanghavi MoMe 102 19 0 05 Jun 2023
Input-gradient space particle inference for neural network ensembles Trung Trinh Markus Heinonen Luigi Acerbi Samuel Kaski UQCV 75 4 0 05 Jun 2023