Fetching the paper…
Reading the bibliography…
Prediction intervals are a machine- and human-interpretable way to represent predictive uncertainty in a regression analysis.
Quality of Uncertainty Quantification for Bayesian Neural Network Inference, 2019, arXiv:1906.09686
Jiayu Yao, Weiwei Pan, Soumya Ghosh, and Finale Doshi-Velez · 1906
Earlier work this paper cites.
Deep Ensembles: A Loss Landscape Perspective, 2019, arXiv:1912.02757
Stanislav Fort, Huiyi Hu, and Balaji Lakshminarayanan · 1912
Earlier work this paper cites.
Quantile Regression
Roger Koenker · 2005
Earlier work this paper cites.
Aleatory or epistemic? Does it matter?
Armen Der Kiureghian and Ove Ditlevsen · 2009
Earlier work this paper cites.
Practical Variational Inference for Neural Networks
Alex Graves · 2011
Earlier work this paper cites.
Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals
A. Khosravi, S. Nahavandi, D. Creighton, and A. F. Atiya · 2011
Earlier work this paper cites.
The Two-Piece Normal, Binormal, or Double Gaussian Distribution: Its Origin and Rediscoveries
Kenneth F. Wallis · 2014
Earlier work this paper cites.
Weight Uncertainty in Neural Network
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, and Daan Wierstra · 2015
Earlier work this paper cites.
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks
Jose Miguel Hernandez-Lobato and Ryan Adams · 2015
Cited alongside, same era.
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Yarin Gal and Zoubin Ghahramani · 2016
Cited alongside, same era.
Bayesian Hypernetworks, 2017, arXiv:1710.04759
David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, and Aaron Courville · 2017
Cited alongside, same era.
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks
Christos Louizos and Max Welling · 2017
Cited alongside, same era.
Implicit Weight Uncertainty in Neural Networks, 2017, arXiv:1711.01297
Nick Pawlowski, Andrew Brock, Matthew C. H. Lee, Martin Rajchl, and Ben Glocker · 2017
Cited alongside, same era.
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach
Tim Pearce, Alexandra Brintrup, Mohamed Zaki, and Andy Neely · 2018
Later among the works it cites.
Predictive Uncertainty Estimation via Prior Networks
Andrey Malinin and Mark Gales · 2018
Later among the works it cites.
JAX: Composable Transformations of Python+NumPy Programs, 2018
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, and Skye Wanderman-Milne · 2018
Later among the works it cites.
Deterministic Variational Inference for Robust Bayesian Neural Networks
Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, Jose Miguel Hernandez-Lobato, and Alexander L. Gaunt · 2019
Later among the works it cites.
Subspace Inference for Bayesian Deep Learning
Pavel Izmailov, Wesley Maddox, Polina Kirichenko, Timur Garipov, Dmitry Vetrov, and Andrew Gordon Wilson · 2019
Later among the works it cites.
Single-Model Uncertainties for Deep Learning
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 2017
Cited alongside, same era.
UCI Machine Learning Repository, 2017
Dheeru Dua and Casey Graff · 2017
Cited alongside, same era.
The Sacred Infrastructure for Computational Research
Klaus Greff, Aaron Klein, Martin Chovanec, Frank Hutter, and Jürgen Schmidhuber · 2017
Cited alongside, same era.
Natasa Tagasovska and David Lopez-Paz · 2019
Later among the works it cites.
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift
Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, D Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, and Jasper Snoek · 2019
Later among the works it cites.
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
Later among the works it cites.