Repulsive Deep Ensembles are Bayesian

22 June 2021

Papers citing "Repulsive Deep Ensembles are Bayesian"

50 / 72 papers shown

Title
Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification Jonas Teufel Annika Leinweber Pascal Friederich 44 0 0 03 Apr 2025
On Local Posterior Structure in Deep Ensembles Mikkel Jordahn Jonas Vestergaard Jensen Mikkel N. Schmidt Michael Riis Andersen UQCV BDL OOD 51 0 0 17 Mar 2025
Entropy-regularized Gradient Estimators for Approximate Bayesian Inference Jasmeet Kaur BDL UQCV 70 0 0 15 Mar 2025
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model Moritz A. Zanger Pascal R. van der Vaart Wendelin Bohmer M. Spaan UQCV BDL 90 0 0 14 Mar 2025
Making Reliable and Flexible Decisions in Long-tailed Classification Bolian Li Ruqi Zhang 84 0 0 23 Jan 2025
Stein Variational Newton Neural Network Ensembles Klemens Flöge Mohammed Abdul Moeed Vincent Fortuin BDL UQCV 35 0 0 04 Nov 2024
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKA David Smerkous Qinxun Bai Fuxin Li BDL 21 0 0 31 Oct 2024
ELBOing Stein: Variational Bayes with Stein Mixture Inference Ola Rønning Eric T. Nalisnick Christophe Ley Padhraic Smyth Thomas Hamelryck BDL 45 1 0 30 Oct 2024
Revisiting Deep Ensemble Uncertainty for Enhanced Medical Anomaly Detection Yi Gu Yi Lin Kwang-Ting Cheng Hao Chen UQCV 22 2 0 26 Sep 2024
Scalable Ensemble Diversification for OOD Generalization and Detection Alexander Rubinstein Luca Scimeca Damien Teney Seong Joon Oh BDL OOD 351 1 0 25 Sep 2024
Continual learning with the neural tangent ensemble Ari S. Benjamin Christian Pehle Kyle Daruwalla UQCV 49 0 0 30 Aug 2024
Flexible Heteroscedastic Count Regression with Deep Double Poisson Networks Spencer Young P. Jenkins Lonchao Da Jeff Dotson Hua Wei UQCV BDL 26 2 0 13 Jun 2024
MODL: Multilearner Online Deep Learning Antonios Valkanas Boris N. Oreshkin Mark J. Coates 34 1 0 28 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 32 9 0 06 May 2024
Pessimistic Value Iteration for Multi-Task Data Sharing in Offline Reinforcement Learning Chenjia Bai Lingxiao Wang Jianye Hao Zhuoran Yang Bin Zhao Zhen Wang Xuelong Li OffRL 27 9 0 30 Apr 2024
Diverse Randomized Value Functions: A Provably Pessimistic Approach for Offline Reinforcement Learning Xudong Yu Chenjia Bai Hongyi Guo Changhong Wang Zhen Wang OffRL 27 0 0 09 Apr 2024
On Uncertainty Quantification for Near-Bayes Optimal Algorithms Ziyu Wang Chris Holmes UQCV 27 2 0 28 Mar 2024
Bridging the Sim-to-Real Gap with Bayesian Inference Jonas Rothfuss Bhavya Sukhija Lenart Treven Florian Dorfler Stelian Coros Andreas Krause AI4CE 29 2 0 25 Mar 2024
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling Hyungi Lee G. Nam Edwin Fong Juho Lee BDL 20 5 0 12 Mar 2024
BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts Emanuele Marconato Samuele Bortolotti Emile van Krieken Antonio Vergari Andrea Passerini Stefano Teso 33 18 0 19 Feb 2024
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning Idan Achituve I. Diamant Arnon Netzer Gal Chechik Ethan Fetaya UQCV 22 4 0 06 Feb 2024
How Good is a Single Basin? Kai Lion Lorenzo Noci Thomas Hofmann Gregor Bachmann UQCV 11 2 0 05 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 35 27 0 01 Feb 2024
Uncertainty in Graph Contrastive Learning with Bayesian Neural Networks Alexander M¨ollers Alexander Immer Elvin Isufi Vincent Fortuin SSL BDL UQCV 16 1 0 30 Nov 2023
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors Olivier Laurent Emanuel Aldea Gianni Franchi BDL UQCV 10 5 0 12 Oct 2023
Something for (almost) nothing: Improving deep ensemble calibration using unlabeled data Konstantinos Pitas Julyan Arbel BDL UQCV FedML 21 0 0 04 Oct 2023
A Primer on Bayesian Neural Networks: Review and Debates Federico Danieli Konstantinos Pitas M. Vladimirova Vincent Fortuin BDL AAML 54 18 0 28 Sep 2023
Adapt then Unlearn: Exploring Parameter Space Semantics for Unlearning in Generative Adversarial Networks Piyush Tiwary Atri Guha Subhodip Panda Prathosh A.P. MU GAN 53 7 0 25 Sep 2023
Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness Ruoxi Qin Linyuan Wang Xuehui Du Xing-yuan Chen Binghai Yan AAML 11 0 0 01 Aug 2023
EnSolver: Uncertainty-Aware Ensemble CAPTCHA Solvers with Theoretical Guarantees D. C. Hoang Behzad Ousat Amin Kharraz Cuong V Nguyen AAML 11 1 0 27 Jul 2023
Quantification of Uncertainty with Adversarial Models Kajetan Schweighofer L. Aichberger Mykyta Ielanskyi G. Klambauer Sepp Hochreiter UQCV 24 14 0 06 Jul 2023
Push: Concurrent Probabilistic Programming for Bayesian Deep Learning Daniel Huang Christian Camaño Jonathan Tsegaye Jonathan Austin Gale AI4CE 20 0 0 10 Jun 2023
Input-gradient space particle inference for neural network ensembles Trung Trinh Markus Heinonen Luigi Acerbi Samuel Kaski UQCV 8 3 0 05 Jun 2023
Improving Neural Additive Models with Bayesian Principles Kouroche Bouchiat Alexander Immer Hugo Yèche Gunnar Rätsch Vincent Fortuin BDL MedIm 19 6 0 26 May 2023
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods Veit Wild Sahra Ghalebikesabi Dino Sejdinovic Jeremias Knoblauch BDL UQCV 19 13 0 24 May 2023
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial V. Nemani Luca Biggio Xun Huan Zhen Hu Olga Fink Anh Tran Yan Wang Xiaoge Zhang Chao Hu AI4CE 23 75 0 07 May 2023
Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization Agustinus Kristiadi Alexander Immer Runa Eschenhagen Vincent Fortuin BDL UQCV 13 8 0 17 Apr 2023
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification Antoine de Mathelin Francois Deheeger Mathilde Mougeot Nicolas Vayatis OOD UQCV 10 2 0 08 Apr 2023
Incorporating Unlabelled Data into Bayesian Neural Networks Mrinank Sharma Tom Rainforth Yee Whye Teh Vincent Fortuin SSL UQCV BDL 32 9 0 04 Apr 2023
Bayesian Quadrature for Neural Ensemble Search Saad Hamid Xingchen Wan Martin Jørgensen Binxin Ru Michael A. Osborne BDL UQCV 13 1 0 15 Mar 2023
Long-tailed Classification from a Bayesian-decision-theory Perspective Bolian Li Ruqi Zhang 20 1 0 10 Mar 2023
Variational Inference on the Final-Layer Output of Neural Networks Yadi Wei R. Khardon BDL UQCV 11 0 0 05 Feb 2023
Pathologies of Predictive Diversity in Deep Ensembles Taiga Abe E. Kelly Buchanan Geoff Pleiss John P. Cunningham UQCV 17 13 0 01 Feb 2023
Joint Training of Deep Ensembles Fails Due to Learner Collusion Alan Jeffares Tennison Liu Jonathan Crabbé M. Schaar FedML 29 15 0 26 Jan 2023
Bayesian posterior approximation with stochastic ensembles Oleksandr Balabanov Bernhard Mehlig H. Linander BDL UQCV 10 5 0 15 Dec 2022
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty Yugo Fujimotol Kei Nakagawa Kentaro Imajo Kentaro Minami AIFin 15 3 0 31 Oct 2022
Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel Seijin Kobayashi Pau Vilimelis Aceituno J. Oswald UQCV 11 2 0 18 Oct 2022
Success of Uncertainty-Aware Deep Models Depends on Data Manifold Geometry M. Penrod Harrison Termotto Varshini Reddy Jiayu Yao Finale Doshi-Velez Weiwei Pan AAML OOD 23 1 0 02 Aug 2022
On the Versatile Uses of Partial Distance Correlation in Deep Learning Xingjian Zhen Zihang Meng Rudrasis Chakraborty Vikas Singh OODD 17 27 0 20 Jul 2022
Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation G. Nam Hyungi Lee Byeongho Heo Juho Lee UQCV FedML 8 7 0 30 Jun 2022