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Score-based generative modeling, informally referred to as diffusion models, continue to grow in popularity across several important domains and tasks.
Regression quantiles
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Wassily Hoeffding · 1994
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Harris Papadopoulos, Kostas Proedrou, Volodya Vovk, and Alex Gammerman · 2002
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On hoeffding’s inequalities
Vidmantas Bentkus · 2004
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Estimation of non-normalized statistical models by score matching
Aapo Hyvärinen and Peter Dayan · 2005
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Vladimir Vovk, Alexander Gammerman, and Glenn Shafer · 2005
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Christopher M Bishop and Nasser M Nasrabadi · 2006
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A tutorial on conformal prediction
Glenn Shafer and Vladimir Vovk · 2008
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2011
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Distribution-free prediction bands for non-parametric regression
Jing Lei and Larry Wasserman · 2014
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Cross-conformal predictors
Vladimir Vovk · 2015
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Vector quantile regression: an optimal transport approach
Guillaume Carlier, Victor Chernozhukov, and Alfred Galichon · 2016
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CVXPY: A Python-embedded modeling language for convex optimization
Steven Diamond and Stephen Boyd · 2016
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Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani · 2016
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Stochastic optimization for large-scale optimal transport
Aude Genevay, Marco Cuturi, Gabriel Peyré, and Francis Bach · 2016
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A kernelized stein discrepancy for goodness-of-fit tests
Qiang Liu, Jason Lee, and Michael Jordan · 2016
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Monge–kantorovich depth, quantiles, ranks and signs
Victor Chernozhukov, Alfred Galichon, Marc Hallin, and Marc Henry · 2017
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A rewriting system for convex optimization problems
Akshay Agrawal, Robin Verschueren, Steven Diamond, and Stephen Boyd · 2018
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Large-scale celebfaces attributes (celeba) dataset
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2018
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The MOSEK optimization toolbox for MATLAB manual. Version 9.0. , 2019
MOSEK ApS · 2019
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Conformalized quantile regression
Yaniv Romano, Evan Patterson, and Emmanuel Candes · 2019
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Diffdock: Diffusion steps, twists, and turns for molecular docking
Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, and Tommi Jaakkola · 2022
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Diffusion models in vision: A survey
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu, and Mubarak Shah · 2022
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Nested conformal prediction and quantile out-of-bag ensemble methods
Chirag Gupta, Arun K Kuchibhotla, and Aaditya Ramdas · 2022
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Equivariant diffusion for molecule generation in 3d
Emiel Hoogeboom, Vıctor Garcia Satorras, Clément Vignac, and Max Welling · 2022
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Conffusion: Confidence intervals for diffusion models
Eliahu Horwitz and Yedid Hoshen · 2022
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
Cited alongside, same era.
Vector quantile regression and optimal transport, from theory to numerics
Guillaume Carlier, Victor Chernozhukov, Gwendoline De Bie, and Alfred Galichon · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Efficient learning of generative models via finite-difference score matching
Tianyu Pang, Kun Xu, Chongxuan Li, Yang Song, Stefano Ermon, and Jun Zhu · 2020
Cited alongside, same era.
Improved techniques for training score-based generative models
Yang Song and Stefano Ermon · 2020
Cited alongside, same era.
A gentle introduction to conformal prediction and distribution-free uncertainty quantification
Anastasios N Angelopoulos and Stephen Bates · 2021
Cited alongside, same era.
Illuminating protein space with a programmable generative model
John Ingraham, Max Baranov, Zak Costello, Vincent Frappier, Ahmed Ismail, Shan Tie, Wujie Wang, Vincent Xue, Fritz Obermeyer, Andrew Beam, et al · 2022
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Diffusion models for medical image analysis: A comprehensive survey
Amirhossein Kazerouni, Ehsan Khodapanah Aghdam, Moein Heidari, Reza Azad, Mohsen Fayyaz, Ilker Hacihaliloglu, and Dorit Merhof · 2022
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What’s behind the mask: Estimating uncertainty in image-to-image problems
Gilad Kutiel, Regev Cohen, Michael Elad, and Daniel Freedman · 2022
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Efficiently controlling multiple risks with pareto testing
Bracha Laufer-Goldshtein, Adam Fisch, Regina Barzilay, and Tommi Jaakkola · 2022
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Convergence for score-based generative modeling with polynomial complexity
Holden Lee, Jianfeng Lu, and Yixin Tan · 2022
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Latent-nerf for shape-guided generation of 3d shapes and textures
Gal Metzer, Elad Richardson, Or Patashnik, Raja Giryes, and Daniel Cohen-Or · 2022
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Fast nonlinear vector quantile regression
Aviv A Rosenberg, Sanketh Vedula, Yaniv Romano, and Alex M Bronstein · 2022
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Towards a most probable recovery in optical imaging
Nadav Torem, Roi Ronen, Yoav Y Schechner, and Michael Elad · 2022
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Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models
Joseph L Watson, David Juergens, Nathaniel R Bennett, Brian L Trippe, Jason Yim, Helen E Eisenach, Woody Ahern, Andrew J Borst, Robert J Ragotte, Lukas F Milles, et al · 2022
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Yutong Xie and Quanzheng Li · 2022
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Dream3d: Zero-shot text-to-3d synthesis using 3d shape prior and text-to-image diffusion models
Jiale Xu, Xintao Wang, Weihao Cheng, Yan-Pei Cao, Ying Shan, Xiaohu Qie, and Shenghua Gao · 2022
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Diffusion models: A comprehensive survey of methods and applications
Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Yingxia Shao, Wentao Zhang, Bin Cui, and Ming-Hsuan Yang · 2022
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Lion: Latent point diffusion models for 3d shape generation
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, and Karsten Kreis · 2022
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Diffusion models in vision: A survey
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu, and Mubarak Shah · 2023
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