paper-bibs.bib

@article{Cha2023OnOTT,
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    author={Seohyeon Cha and Honggu Kang and Joonhyuk Kang},
    year={2023},
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    journal={arXiv.org},
}

 

@article{Zhao2020UncertaintyUAS,
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    year={2020},
    url={https://www.semanticscholar.org/paper/898178fa298635099da4ce5411564d837998b018},
    journal={Neural Information Processing Systems},
}

 

@inproceedings{Kong2024UnknownAwareUGR,
    title={Unknown-Aware Graph Regularization for Robust Semi-supervised Learning from Uncurated Data},
    author={Heejo Kong and Suneung Kim and Ho-Joong Kim and Seong-Whan Lee},
    year={2024},
    url={https://www.semanticscholar.org/paper/b82ea48f183d1708229ead6ea820b55f4b3ef8e5},
    booktitle={AAAI Conference on Artificial Intelligence},
}

 

@article{Stadler2021GraphGPN,
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    year={2021},
    url={https://www.semanticscholar.org/paper/66ee16c1a274f1c9205b0ef4fbda0b4a8a481f81},
    journal={Neural Information Processing Systems},
}

 

@inproceedings{Lin2024GraphGNS,
    title={Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification},
    author={Xixun Lin and Wenxiao Zhang and Fengzhao Shi and Chuan Zhou and Lixin Zou and Xiangyu Zhao and Dawei Yin and Shirui Pan and Yanan Cao},
    year={2024},
    url={https://www.semanticscholar.org/paper/6fd85ef91f8392d4cbe923713d93a41e3ceabe1f},
    booktitle={International Conference on Machine Learning},
}

 

@inproceedings{Guo2017OnOCO,
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    year={2017},
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@article{Minderer2021RevisitingRTC,
    title={Revisiting the Calibration of Modern Neural Networks},
    author={Matthias Minderer and Josip Djolonga and Rob Romijnders and F. Hubis and Xiaohua Zhai and N. Houlsby and Dustin Tran and Mario Lucic},
    year={2021},
    url={https://www.semanticscholar.org/paper/e757488d2e8684e3da7b14fbb000b7e4a0bab001},
    journal={Neural Information Processing Systems},
}

 

@article{Liang2017EnhancingETR,
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    year={2017},
    url={https://www.semanticscholar.org/paper/547c854985629cfa9404a5ba8ca29367b5f8c25f},
    journal={International Conference on Learning Representations},
}

 

@article{Csizi2024EuclidEPD,
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Bologna and 62 vialeBertiPichat and 40129 Bologna and M. F. Physics and 1. Giessenbachstr. and 85748 Garching and Germany and Universitatssternwarte Munchen and F. Physik and Ludwig-Maximilians-Universitat Munchen and 1. Scheinerstrasse and 8. Munchen and I. Torino and 20 viaOsservatorio and 1. P. Torinese and D. Fisica and U. Genova and 33 viaDodecaneso and 16146 and Genova and I. Genova and Department of PhysicsE. Pancini and U. Federico and 6. ViaCinthia and 80126 and Napoli and I. -. Capodimonte and 16 viaMoiariello and 80131 Napoli and I. Naples and I. D. A. E. C. D. Espacco and U. Porto and Caup and Rua das Estrelas and P. Porto and Portugal and F. Porto and Rua do Campo Alegre and 4169-007 Porto and U. Torino and 1. ViaP.Giuria and 10125 Torino and I. 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LargoGalileoGalilei and 00044 Frascati and Roma and Esacesa and Camino Bajo de Castillo and sn. and Urb. Villafranca del Castillo and 28692 Villanueva de la Canada and Madrid and 1. Universit'eClaudeBernardLyon and CNRSIN2p3 and I. Lyon and Umr 5822 and Villeurbanne and F-69100 and France and I. O. Physics and L. O. Astrophysics and E. P. F. Lausanne and Observatoire de Sauverny and 1290 Versoix and Switzerland and Institut de Ci'encies del Cosmos and U. Barcelona and 1. Mart'iiFranques and 08193 Barcelona and I. C. D. R. I. E. Avanccats and 23 PasseigdeLlu'isCompanys and 08193 Barcelona and 1. UCBLyon and Iuf and 4. R. E. Fermi and 69622 Villeurbanne and Mullard Space Science Laboratory and U. London and H. Mary and Dorking and Surrey RH5 6NT and D. D. F'isica and F. Ciencias and Universidade de Lisboa and C8 Edif'icio and C. Grande and P. Lisboa and 1049-001 Lisboa and D. O. Astronomy and U. Geneva and 16 ch.d'Ecogia and Universit'e Paris-Saclay and Cnrs and I. D. 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    year={2024},
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    journal={},
}

 

@article{Sensoy2018EvidentialEDL,
    title={Evidential Deep Learning to Quantify Classification Uncertainty},
    author={M. Sensoy and M. Kandemir and Lance M. Kaplan},
    year={2018},
    url={https://www.semanticscholar.org/paper/138fafc2d679bc6446ff74f55dfd316b0d5674b9},
    journal={Neural Information Processing Systems},
}

 

@article{Li2024HyperHED,
    title={Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty},
    author={Changbin Li and Kangshuo Li and Yuzhe Ou and Lance M. Kaplan and A. Jøsang and Jin-Hee Cho and Dong Hyun. Jeong and Feng Chen},
    year={2024},
    url={https://www.semanticscholar.org/paper/fe9e834462ce8fa399af1287d53b6e9236fbe326},
    journal={International Conference on Learning Representations},
}

 

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    journal={arXiv.org},
}

 

@article{Pawlowski2017ImplicitIWU,
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    author={Nick Pawlowski and Martin Rajchl and Ben Glocker},
    year={2017},
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    journal={arXiv.org},
}

 

@article{Ovadia2019CanCYT,
    title={Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift},
    author={Yaniv Ovadia and Emily Fertig and Jie Jessie Ren and Zachary Nado and D. Sculley and Sebastian Nowozin and Joshua V. Dillon and Balaji Lakshminarayanan and Jasper Snoek},
    year={2019},
    url={https://www.semanticscholar.org/paper/1eb7f46b1a0a7df823194d86543e5554aa21021a},
    journal={Neural Information Processing Systems},
}

 

@article{Fayjie2024PredictivePUE,
    title={Predictive uncertainty estimation in deep learning for lung carcinoma classification in digital pathology under real dataset shifts},
    author={A. Fayjie and Jutika Borah and F. Carbone and Jan Tack and Patrick Vandewalle},
    year={2024},
    url={https://www.semanticscholar.org/paper/9654d1b2457a41db446e4f79a8f35e17047c31d7},
    journal={arXiv.org},
}

 

@article{Ashukha2020PitfallsPOI,
    title={Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning},
    author={Arsenii Ashukha and Alexander Lyzhov and Dmitry Molchanov and D. Vetrov},
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    url={https://www.semanticscholar.org/paper/d12fd94337ac804470dc78911e74b5b6480eef8e},
    journal={International Conference on Learning Representations},
}

 

@article{Wilson2020BayesianBDL,
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    author={A. Wilson and Pavel Izmailov},
    year={2020},
    url={https://www.semanticscholar.org/paper/af9280741ef627f0d6c8437605d002d3bfc2d1b1},
    journal={Neural Information Processing Systems},
}

 

@article{Gelman2016AttitudesATA,
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}

 

@inproceedings{Gal2015DropoutDAA,
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    booktitle={International Conference on Machine Learning},
}



@article{Knoblauch2022AnAOV,
    title={An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference},
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    year={2022},
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    journal={Journal of machine learning research},
}



@article{Hinton2015DistillingDTK,
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    journal={arXiv.org},
}

 

@article{Lin2020AnAEF,
    title={An efficient framework for counting pedestrians crossing a line using low-cost devices: the benefits of distilling the knowledge in a neural network},
    author={Yih-Kai Lin and Chu-Fu Wang and Ching-Yu Chang and Hao Sun},
    year={2020},
    url={https://www.semanticscholar.org/paper/1d194274f2db9fc43adc1b93f31ff2800c9c8db6},
    journal={Multimedia tools and applications},
}

 

@inproceedings{Lakshminarayanan2016SimpleSAS,
    title={Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles},
    author={Balaji Lakshminarayanan and A. Pritzel and C. Blundell},
    year={2016},
    url={https://www.semanticscholar.org/paper/802168a81571dde28f5ddb94d84677bc007afa7b},
    booktitle={Neural Information Processing Systems},
}

@inproceedings{wenzel2020good,
  title={How Good is the Bayes Posterior in Deep Neural Networks Really?},
  author={Wenzel, Florian and Roth, Kevin and Veeling, Bastiaan and Swiatkowski, Jakub and Tran, Linh and Mandt, Stephan and Snoek, Jasper and Salimans, Tim and Jenatton, Rodolphe and Nowozin, Sebastian},
  booktitle={International Conference on Machine Learning},
  pages={10248--10259},
  year={2020},
  organization={PMLR}
}




@article{Hinton2015DistillingDTK,
    title={Distilling the Knowledge in a Neural Network},
    author={Geoffrey E. Hinton and O. Vinyals and J. Dean},
    year={2015},
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    journal={arXiv.org},
}

 

@article{Lin2020AnAEF,
    title={An efficient framework for counting pedestrians crossing a line using low-cost devices: the benefits of distilling the knowledge in a neural network},
    author={Yih-Kai Lin and Chu-Fu Wang and Ching-Yu Chang and Hao Sun},
    year={2020},
    url={https://www.semanticscholar.org/paper/1d194274f2db9fc43adc1b93f31ff2800c9c8db6},
    journal={Multimedia tools and applications},
}

 

@inproceedings{Lakshminarayanan2016SimpleSAS,
    title={Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles},
    author={Balaji Lakshminarayanan and A. Pritzel and C. Blundell},
    year={2016},
    url={https://www.semanticscholar.org/paper/802168a81571dde28f5ddb94d84677bc007afa7b},
    booktitle={Neural Information Processing Systems},
}

@inproceedings{wenzel2020good,
  title={How Good is the Bayes Posterior in Deep Neural Networks Really?},
  author={Wenzel, Florian and Roth, Kevin and Veeling, Bastiaan and Swiatkowski, Jakub and Tran, Linh and Mandt, Stephan and Snoek, Jasper and Salimans, Tim and Jenatton, Rodolphe and Nowozin, Sebastian},
  booktitle={International Conference on Machine Learning},
  pages={10248--10259},
  year={2020},
  organization={PMLR}
}



@article{Liu2021AABF,
    title={A Bayesian Federated Learning Framework With Online Laplace Approximation},
    author={Liang Liu and Xi Jiang and Feng Zheng and Hong Chen and Guo-Jun Qi and Heng Huang and Ling Shao},
    year={2021},
    url={https://www.semanticscholar.org/paper/d7b055c6eb3c0f4decb29f14e4c4f52c50501d1f},
    journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
}

 

@article{Al-Shedivat2020FederatedFLV,
    title={Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms},
    author={Maruan Al-Shedivat and Jennifer Gillenwater and E. Xing and Afshin Rostamizadeh},
    year={2020},
    url={https://www.semanticscholar.org/paper/59477007095a68ba551a588df756fb9873a14b72},
    journal={International Conference on Learning Representations},
}


@article{Ritter2018AASL,
    title={A Scalable Laplace Approximation for Neural Networks},
    author={H. Ritter and Aleksandar Botev and D. Barber},
    year={2018},
    url={https://www.semanticscholar.org/paper/ad8631abf269d2b886614f69221d25a732a7f58d},
    journal={International Conference on Learning Representations},
}

 

@article{Antorán2024ScalableSBI,
    title={Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks},
    author={Javier Antorán},
    year={2024},
    url={https://www.semanticscholar.org/paper/c4d23a3eb3225dbc9a0c7e943353aa657913497b},
    journal={arXiv.org},
}

 

@article{Liu2023FedLPAFOF,
    title={FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation},
    author={Xiang Liu and Liangxi Liu and Feiyang Ye and Yunheng Shen and Xia Li and Linshan Jiang and Jialin Li},
    year={2024},
    url={https://www.semanticscholar.org/paper/2e0ffd2cd3d70898f48d4a059095ff117452c849},
    journal={Neural Information Processing Systems},
}