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Bayesian Deep Ensembles via the Neural Tangent Kernel

11 July 2020

Bobby He

Balaji Lakshminarayanan

Papers citing "Bayesian Deep Ensembles via the Neural Tangent Kernel"

50 / 85 papers shown

Title
Model Reprogramming Demystified: A Neural Tangent Kernel Perspective Ming-Yu Chung Jiashuo Fan Hancheng Ye Qinsi Wang Wei-Chen Shen Chia-Mu Yu Pin-Yu Chen Sy-Yen Kuo 32 1 0 31 May 2025
Universal Value-Function Uncertainties Moritz A. Zanger Max Weltevrede Yaniv Oren Pascal R. van der Vaart Caroline Horsch Wendelin Bohmer M. Spaan OffRL 74 0 0 27 May 2025
TULiP: Test-time Uncertainty Estimation via Linearization and Weight Perturbation Yuhui Zhang Dongshen Wu Yuichiro Wada Takafumi Kanamori OODD 243 1 0 22 May 2025
Epistemic Artificial Intelligence is Essential for Machine Learning Models to Truly 'Know When They Do Not Know' Shireen Kudukkil Manchingal Andrew Bradley Julian F. P. Kooij Keivan K1 Shariatmadar Neil Yorke-Smith Fabio Cuzzolin 171 1 0 08 May 2025
Uncertainty Quantification for Machine Learning in Healthcare: A Survey L. J. L. Lopez Shaza Elsharief Dhiyaa Al Jorf Firas Darwish Congbo Ma Farah E. Shamout 544 0 0 04 May 2025
Position: Enough of Scaling LLMs! Lets Focus on Downscaling Ayan Sengupta Ayan Sengupta Tanmoy Chakraborty 112 0 0 02 May 2025
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model Moritz A. Zanger Pascal R. van der Vaart Wendelin Bohmer M. Spaan UQCV BDL 507 2 0 14 Mar 2025
Observation Noise and Initialization in Wide Neural Networks Sergio Calvo-Ordoñez Jonathan Plenk Richard Bergna Alvaro Cartea Jose Miguel Hernandez-Lobato Konstantina Palla Kamil Ciosek 120 1 0 03 Feb 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks Kaizheng Wang Keivan K1 Shariatmadar Shireen Kudukkil Manchingal Fabio Cuzzolin David Moens Hans Hallez UQCV BDL 270 14 0 28 Jan 2025
DistPred: A Distribution-Free Probabilistic Inference Method for Regression and Forecasting Daojun Liang Haixia Zhang Dongfeng Yuan UQCV 146 0 0 08 Jan 2025
Epistemic Uncertainty and Observation Noise with the Neural Tangent Kernel Sergio Calvo-Ordoñez Konstantina Palla Kamil Ciosek 71 1 0 06 Sep 2024
Continual learning with the neural tangent ensemble Ari S. Benjamin Christian Pehle Kyle Daruwalla UQCV 141 1 0 30 Aug 2024
Low-Budget Simulation-Based Inference with Bayesian Neural Networks Arnaud Delaunoy Maxence de la Brassinne Bonardeaux S. Mishra-Sharma Gilles Louppe 81 2 0 27 Aug 2024
Neural Lineage Runpeng Yu Xinchao Wang 102 4 0 17 Jun 2024
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification Kaizheng Wang Fabio Cuzzolin Keivan K1 Shariatmadar David Moens Hans Hallez UQCV BDL 128 6 0 23 May 2024
Gaussian Stochastic Weight Averaging for Bayesian Low-Rank Adaptation of Large Language Models Emre Onal Klemens Flöge Emma Caldwell A. Sheverdin Vincent Fortuin UQCV BDL 125 12 0 06 May 2024
PINNACLE: PINN Adaptive ColLocation and Experimental points selection Gregory Kang Ruey Lau Apivich Hemachandra See-Kiong Ng K. H. Low 3DPC 121 20 0 11 Apr 2024
On Uncertainty Quantification for Near-Bayes Optimal Algorithms Ziyu Wang Chris Holmes UQCV 105 3 0 28 Mar 2024
A prediction rigidity formalism for low-cost uncertainties in trained neural networks Filippo Bigi Sanggyu Chong Michele Ceriotti Federico Grasselli 75 6 0 04 Mar 2024
Active Few-Shot Fine-Tuning Jonas Hübotter Bhavya Sukhija Lenart Treven Yarden As Andreas Krause 104 1 0 13 Feb 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel ... David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang UQCV BDL 148 35 0 01 Feb 2024
Generative Posterior Networks for Approximately Bayesian Epistemic Uncertainty Estimation Melrose Roderick Felix Berkenkamp Fatemeh Sheikholeslami Zico Kolter UQCV 34 0 0 29 Dec 2023
Uncertainty in Graph Contrastive Learning with Bayesian Neural Networks Alexander M¨ollers Alexander Immer Elvin Isufi Vincent Fortuin SSL BDL UQCV 123 1 0 30 Nov 2023
Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective Ming-Yu Chung Sheng-Yen Chou Chia-Mu Yu Pin-Yu Chen Sy-Yen Kuo Tsung-Yi Ho DD 159 7 0 28 Nov 2023
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling Bairu Hou Yujian Liu Kaizhi Qian Jacob Andreas Shiyu Chang Yang Zhang UD UQCV PER 98 65 0 15 Nov 2023
On permutation symmetries in Bayesian neural network posteriors: a variational perspective Simone Rossi Ankit Singh T. Hannagan 69 3 0 16 Oct 2023
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification Qianli Shen Wai Hoh Tang Zhun Deng Apostolos F. Psaros Kenji Kawaguchi 211 1 0 10 Oct 2023
Commutative Width and Depth Scaling in Deep Neural Networks Soufiane Hayou 83 2 0 02 Oct 2023
Towards Efficient and Trustworthy AI Through Hardware-Algorithm-Communication Co-Design Yongchao Chen Osvaldo Simeone Bashir M. Al-Hashimi 86 4 0 27 Sep 2023
PAGER: A Framework for Failure Analysis of Deep Regression Models Jayaraman J. Thiagarajan V. Narayanaswamy Puja Trivedi Rushil Anirudh 65 0 0 20 Sep 2023
Information-theoretic Analysis of Test Data Sensitivity in Uncertainty Futoshi Futami Tomoharu Iwata UD PER 62 3 0 23 Jul 2023
Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks Ziyi Huang Henry Lam Haofeng Zhang UQCV 84 7 0 09 Jun 2023
Training-Free Neural Active Learning with Initialization-Robustness Guarantees Apivich Hemachandra Zhongxiang Dai Jasraj Singh See-Kiong Ng K. H. Low AAML 87 7 0 07 Jun 2023
Improving Neural Additive Models with Bayesian Principles Kouroche Bouchiat Alexander Immer Hugo Yèche Gunnar Rätsch Vincent Fortuin BDL MedIm 105 6 0 26 May 2023
Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization Agustinus Kristiadi Alexander Immer Runa Eschenhagen Vincent Fortuin BDL UQCV 80 10 0 17 Apr 2023
Bayesian Quadrature for Neural Ensemble Search Saad Hamid Xingchen Wan Martin Jørgensen Binxin Ru Michael A. Osborne BDL UQCV 69 1 0 15 Mar 2023
Toward Robust Uncertainty Estimation with Random Activation Functions Y. Stoyanova Soroush Ghandi M. Tavakol UQCV 70 2 0 28 Feb 2023
Width and Depth Limits Commute in Residual Networks Soufiane Hayou Greg Yang 90 14 0 01 Feb 2023
Estimating Causal Effects using a Multi-task Deep Ensemble Ziyang Jiang Zhuoran Hou Yi-Ling Liu Yiman Ren Keyu Li David Carlson CML 76 6 0 26 Jan 2023
Bayesian Interpolation with Deep Linear Networks Boris Hanin Alexander Zlokapa 151 26 0 29 Dec 2022
Improving Uncertainty Quantification of Variance Networks by Tree-Structured Learning Wenxuan Ma Xing Yan Kun Zhang UQCV 66 0 0 24 Dec 2022
Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel Seijin Kobayashi Pau Vilimelis Aceituno J. Oswald UQCV 87 3 0 18 Oct 2022
Learning Skills from Demonstrations: A Trend from Motion Primitives to Experience Abstraction Mehrdad Tavassoli S. Katyara Maria Pozzi Nikhil Deshpande D. Caldwell D. Prattichizzo 96 13 0 14 Oct 2022
Sample-Then-Optimize Batch Neural Thompson Sampling Zhongxiang Dai Yao Shu Bryan Kian Hsiang Low Patrick Jaillet AAML 72 25 0 13 Oct 2022
On the infinite-depth limit of finite-width neural networks Soufiane Hayou 97 23 0 03 Oct 2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel Sungyub Kim Si-hun Park Kyungsu Kim Eunho Yang BDL 86 5 0 30 Sep 2022
Single Model Uncertainty Estimation via Stochastic Data Centering Jayaraman J. Thiagarajan Rushil Anirudh V. Narayanaswamy P. Bremer UQCV OOD 67 28 0 14 Jul 2022
A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel Mohamad Amin Mohamadi Wonho Bae Danica J. Sutherland AAML 86 28 0 25 Jun 2022
Fast Finite Width Neural Tangent Kernel Roman Novak Jascha Narain Sohl-Dickstein S. Schoenholz AAML 65 56 0 17 Jun 2022
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping Vikranth Dwaracherla Zheng Wen Ian Osband Xiuyuan Lu S. Asghari Benjamin Van Roy UQCV 96 20 0 08 Jun 2022