ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1906.07380
  4. Cited By
Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep
  Ensembles
v1v2 (latest)

Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles

AAAI Conference on Artificial Intelligence (AAAI), 2019
18 June 2019
Siddhartha Jain
Ge Liu
Jonas W. Mueller
David K Gifford
    UQCV
ArXiv (abs)PDFHTML

Papers citing "Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles"

31 / 31 papers shown
Title
On Joint Regularization and Calibration in Deep Ensembles
On Joint Regularization and Calibration in Deep Ensembles
Laurits Fredsgaard
Mikkel N. Schmidt
UQCV
323
0
0
06 Nov 2025
The Role of Predictive Uncertainty and Diversity in Embodied AI and
  Robot Learning
The Role of Predictive Uncertainty and Diversity in Embodied AI and Robot Learning
Ransalu Senanayake
265
11
0
06 May 2024
Uncertainty in Language Models: Assessment through Rank-Calibration
Uncertainty in Language Models: Assessment through Rank-CalibrationConference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Xinmeng Huang
Shuo Li
Mengxin Yu
Matteo Sesia
Hamed Hassani
Insup Lee
Osbert Bastani
Guang Cheng
195
32
0
04 Apr 2024
Koopman Ensembles for Probabilistic Time Series Forecasting
Koopman Ensembles for Probabilistic Time Series ForecastingEuropean Signal Processing Conference (EUSIPCO), 2024
Anthony Frion
Lucas Drumetz
Guillaume Tochon
M. Dalla Mura
Albdeldjalil Aissa El Bey
AI4TS
118
2
0
11 Mar 2024
Leveraging Neural Radiance Fields for Uncertainty-Aware Visual
  Localization
Leveraging Neural Radiance Fields for Uncertainty-Aware Visual LocalizationIEEE International Conference on Robotics and Automation (ICRA), 2023
Le Chen
Weirong Chen
Rui Wang
Marc Pollefeys
UQCV
193
16
0
10 Oct 2023
Using AI Uncertainty Quantification to Improve Human Decision-Making
Using AI Uncertainty Quantification to Improve Human Decision-MakingInternational Conference on Machine Learning (ICML), 2023
L. Marusich
J. Bakdash
Yan Zhou
Murat Kantarcioglu
230
11
0
19 Sep 2023
Long-term drought prediction using deep neural networks based on
  geospatial weather data
Long-term drought prediction using deep neural networks based on geospatial weather dataEnvironmental Modelling & Software (Environ. Model. Softw.), 2023
Alexander Marusov
Vsevolod Grabar
Yury Maximov
Nazar Sotiriadi
Alexander Bulkin
Alexey Zaytsev
193
19
0
12 Sep 2023
Quantifying Uncertainty in Answers from any Language Model and Enhancing
  their Trustworthiness
Quantifying Uncertainty in Answers from any Language Model and Enhancing their TrustworthinessAnnual Meeting of the Association for Computational Linguistics (ACL), 2023
Jiuhai Chen
Jonas W. Mueller
317
103
0
30 Aug 2023
Likelihood-ratio-based confidence intervals for neural networks
Likelihood-ratio-based confidence intervals for neural networksMachine-mediated learning (ML), 2023
Laurens Sluijterman
Eric Cator
Tom Heskes
UQCV
142
2
0
04 Aug 2023
Deep Anti-Regularized Ensembles provide reliable out-of-distribution
  uncertainty quantification
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification
Antoine de Mathelin
Francois Deheeger
Mathilde Mougeot
Nicolas Vayatis
OODUQCV
222
4
0
08 Apr 2023
FAIR-Ensemble: When Fairness Naturally Emerges From Deep Ensembling
FAIR-Ensemble: When Fairness Naturally Emerges From Deep Ensembling
Wei-Yin Ko
Daniel D'souza
Karina Nguyen
Randall Balestriero
Sara Hooker
FedML
257
13
0
01 Mar 2023
Optimal Training of Mean Variance Estimation Neural Networks
Optimal Training of Mean Variance Estimation Neural NetworksNeurocomputing (Neurocomputing), 2023
Laurens Sluijterman
Eric Cator
Tom Heskes
DRL
174
33
0
17 Feb 2023
Pathologies of Predictive Diversity in Deep Ensembles
Pathologies of Predictive Diversity in Deep Ensembles
Taiga Abe
E. Kelly Buchanan
Geoff Pleiss
John P. Cunningham
UQCV
328
21
0
01 Feb 2023
Back to the Basics: Revisiting Out-of-Distribution Detection Baselines
Back to the Basics: Revisiting Out-of-Distribution Detection Baselines
Jo-Lan Kuan
Jonas W. Mueller
OODD
137
31
0
07 Jul 2022
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and
  Bootstrapping
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping
Vikranth Dwaracherla
Zheng Wen
Ian Osband
Xiuyuan Lu
S. Asghari
Benjamin Van Roy
UQCV
212
21
0
08 Jun 2022
Verification-Aided Deep Ensemble Selection
Verification-Aided Deep Ensemble SelectionFormal Methods in Computer-Aided Design (FMCAD), 2022
Guy Amir
Tom Zelazny
Guy Katz
Michael Schapira
AAML
233
18
0
08 Feb 2022
Improving robustness and calibration in ensembles with diversity
  regularization
Improving robustness and calibration in ensembles with diversity regularizationGerman Conference on Pattern Recognition (GCPR), 2022
H. A. Mehrtens
Camila González
Anirban Mukhopadhyay
UQCV
115
9
0
26 Jan 2022
Robust uncertainty estimates with out-of-distribution pseudo-inputs
  training
Robust uncertainty estimates with out-of-distribution pseudo-inputs training
Pierre Segonne
Yevgen Zainchkovskyy
Søren Hauberg
UQCVOOD
100
1
0
15 Jan 2022
Diversity and Generalization in Neural Network Ensembles
Diversity and Generalization in Neural Network Ensembles
Luis A. Ortega
Rafael Cabañas
A. Masegosa
FedMLUQCV
178
54
0
26 Oct 2021
Uncertainty-Aware Machine Translation Evaluation
Uncertainty-Aware Machine Translation Evaluation
T. Glushkova
Chrysoula Zerva
Ricardo Rei
André F.T. Martins
UQLM
309
49
0
13 Sep 2021
Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit
  3D Representations
Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit 3D Representations
Jianxiong Shen
Adria Ruiz
Antonio Agudo
Francesc Moreno-Noguer
BDL
382
82
0
05 Sep 2021
A Dataset-Level Geometric Framework for Ensemble Classifiers
A Dataset-Level Geometric Framework for Ensemble Classifiers
Shengli Wu
Weimin Ding
81
3
0
16 Jun 2021
Ex uno plures: Splitting One Model into an Ensemble of Subnetworks
Ex uno plures: Splitting One Model into an Ensemble of Subnetworks
Zhilu Zhang
Vianne R. Gao
M. Sabuncu
UQCV
229
7
0
09 Jun 2021
Uncertainty-Aware Boosted Ensembling in Multi-Modal Settings
Uncertainty-Aware Boosted Ensembling in Multi-Modal SettingsIEEE International Joint Conference on Neural Network (IJCNN), 2021
U. Sarawgi
Rishab Khincha
W. Zulfikar
Satrajit S. Ghosh
Pattie Maes
UQCV
160
7
0
21 Apr 2021
Flexible Model Aggregation for Quantile Regression
Flexible Model Aggregation for Quantile RegressionJournal of machine learning research (JMLR), 2021
Rasool Fakoor
Tae-Soo Kim
Jonas W. Mueller
Alexander J. Smola
Robert Tibshirani
498
28
0
26 Feb 2021
Semi-supervised novelty detection using ensembles with regularized
  disagreement
Semi-supervised novelty detection using ensembles with regularized disagreementConference on Uncertainty in Artificial Intelligence (UAI), 2020
A. Tifrea
E. Stavarache
Fanny Yang
UQCV
233
6
0
10 Dec 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques,
  Applications and Challenges
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and ChallengesInformation Fusion (Inf. Fusion), 2020
Moloud Abdar
Farhad Pourpanah
Sadiq Hussain
Dana Rezazadegan
Tianpeng Liu
...
Xiaochun Cao
Abbas Khosravi
U. Acharya
V. Makarenkov
S. Nahavandi
BDLUQCV
915
2,256
0
12 Nov 2020
Why have a Unified Predictive Uncertainty? Disentangling it using Deep
  Split Ensembles
Why have a Unified Predictive Uncertainty? Disentangling it using Deep Split Ensembles
U. Sarawgi
W. Zulfikar
Rishab Khincha
Pattie Maes
PERUQCVBDLUD
120
7
0
25 Sep 2020
Fast, Accurate, and Simple Models for Tabular Data via Augmented
  Distillation
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation
Rasool Fakoor
Jonas W. Mueller
Nick Erickson
Pratik Chaudhari
Alex Smola
157
62
0
25 Jun 2020
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift
Sheheryar Zaidi
Arber Zela
T. Elsken
Chris Holmes
Katharina Eggensperger
Yee Whye Teh
OODUQCV
254
85
0
15 Jun 2020
Dropout Strikes Back: Improved Uncertainty Estimation via Diversity
  Sampling
Dropout Strikes Back: Improved Uncertainty Estimation via Diversity SamplingInternational Joint Conference on the Analysis of Images, Social Networks and Texts (AISNT), 2020
Kirill Fedyanin
Evgenii Tsymbalov
Maxim Panov
UQCV
160
7
0
06 Mar 2020
1