Diverse Ensembles Improve Calibration

8 July 2020

Papers citing "Diverse Ensembles Improve Calibration"

24 / 24 papers shown

Title
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization Xin Sun Liang Wang Qiang Liu Shu Wu Zilei Wang Liang Wang OOD CML 31 5 0 08 Aug 2024
Improving Self Consistency in LLMs through Probabilistic Tokenization Ashutosh Sathe Divyanshu Aggarwal Sunayana Sitaram 37 4 0 04 Jul 2024
Weighted Ensemble Models Are Strong Continual Learners Imad Eddine Marouf Subhankar Roy Enzo Tartaglione Stéphane Lathuilière CLL 27 16 0 14 Dec 2023
Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions Pouya Pezeshkpour Estevam R. Hruschka LRM 13 126 0 22 Aug 2023
Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy Stanislav Dereka I. Karpukhin Maksim Zhdanov Sergey Kolesnikov 30 0 0 19 May 2023
Source-free Domain Adaptation Requires Penalized Diversity Laya Rafiee Sevyeri Ivaxi Sheth Farhood Farahnak Alexandre See Samira Ebrahimi Kahou T. Fevens Mohammad Havaei TTA 13 0 0 06 Apr 2023
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries Charlotte Loh Seung-Jun Han Shivchander Sudalairaj Rumen Dangovski Kai Xu F. Wenzel Marin Soljacic Akash Srivastava UQCV 39 1 0 04 Mar 2023
FAIR-Ensemble: When Fairness Naturally Emerges From Deep Ensembling Wei-Yin Ko Daniel D'souza Karina Nguyen Randall Balestriero Sara Hooker FedML 19 11 0 01 Mar 2023
Bayesian posterior approximation with stochastic ensembles Oleksandr Balabanov Bernhard Mehlig H. Linander BDL UQCV 27 5 0 15 Dec 2022
Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift Ananya Kumar Tengyu Ma Percy Liang Aditi Raghunathan UQCV OODD OOD 37 38 0 18 Jul 2022
Agree to Disagree: Diversity through Disagreement for Better Transferability Matteo Pagliardini Martin Jaggi Franccois Fleuret Sai Praneeth Karimireddy 20 70 0 09 Feb 2022
Improving robustness and calibration in ensembles with diversity regularization H. A. Mehrtens Camila González Anirban Mukhopadhyay UQCV 11 7 0 26 Jan 2022
Maximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentation Agostina J. Larrazabal Cesar E. Martínez Jose Dolz Enzo Ferrante 16 15 0 22 Dec 2021
Combining Different V1 Brain Model Variants to Improve Robustness to Image Corruptions in CNNs A. Baidya Joel Dapello J. DiCarlo Tiago Marques AAML 22 6 0 20 Oct 2021
Combining Diverse Feature Priors Saachi Jain Dimitris Tsipras A. Madry 56 14 0 15 Oct 2021
Robust fine-tuning of zero-shot models Mitchell Wortsman Gabriel Ilharco Jong Wook Kim Mike Li Simon Kornblith ... Raphael Gontijo-Lopes Hannaneh Hajishirzi Ali Farhadi Hongseok Namkoong Ludwig Schmidt VLM 23 688 0 04 Sep 2021
Knowing More About Questions Can Help: Improving Calibration in Question Answering Shujian Zhang Chengyue Gong Eunsol Choi UQLM 25 58 0 02 Jun 2021
DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling Akis Linardos Matthias Kümmerer Ori Press Matthias Bethge MDE 16 64 0 26 May 2021
Orthogonal Ensemble Networks for Biomedical Image Segmentation Agostina J. Larrazabal Cesar E. Martínez Jose Dolz Enzo Ferrante UQCV 16 22 0 22 May 2021
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation Alexandre Ramé Matthieu Cord FedML 40 51 0 14 Jan 2021
Should Ensemble Members Be Calibrated? Xixin Wu Mark J. F. Gales UQCV 15 12 0 13 Jan 2021
Deep Ensembles for Low-Data Transfer Learning Basil Mustafa C. Riquelme J. Puigcerver andAndré Susano Pinto Daniel Keysers N. Houlsby FedML OOD 20 22 0 14 Oct 2020
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems Zhe Chen Yuyan Wang Dong Lin D. Cheng Lichan Hong Ed H. Chi Claire Cui 28 16 0 17 Aug 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016