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Score-based generative models have emerged as alternatives to generative adversarial networks (GANs) and normalizing flows for tasks involving learning and sampling from complex image distributions.
Minkowski functionals in cosmology
Jens Schmalzing, Martin Kerscher, and Thomas Buchert · 1995
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Minkowski functionals used in the morphological analysis of cosmic microwave background anisotropy maps
Jens Schmalzing and Krzysztof M Górski · 1998
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Maps of dust infrared emission for use in estimation of reddening and cosmic microwave background radiation foregrounds
David J Schlegel, Douglas P Finkbeiner, and Marc Davis · 1998
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The Coyote Universe II: Cosmological Models and Precision Emulation of the Nonlinear Matter Power Spectrum
Katrin Heitmann, David Higdon, Martin White, Salman Habib, Brian J. Williams, and Christian Wagner · 2009
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 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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Sergey Zagoruyko and Nikos Komodakis · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Exploring cosmic origins with core: B-mode component separation
Mathieu Remazeilles, Anthony J Banday, Carlo Baccigalupi, S Basak, A Bonaldi, G De Zotti, J Delabrouille, C Dickinson, HK Eriksen, J Errard, et al · 2018
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Group normalization
Yuxin Wu and Kaiming He · 2018
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Accelerating science with generative adversarial networks: an application to 3d particle showers in multilayer calorimeters
Michela Paganini, Luke de Oliveira, and Benjamin Nachman · 2018
Earlier work this paper cites.
A 3d dust map based on gaia, pan-starrs 1, and 2mass
Gregory M Green, Edward Schlafly, Catherine Zucker, Joshua S Speagle, and Douglas Finkbeiner · 2019
Cited alongside, same era.
Charting nearby dust clouds using gaia data only
RH Leike and TA Enßlin · 2019
Cited alongside, same era.
Cosmogan: creating high-fidelity weak lensing convergence maps using generative adversarial networks
Mustafa Mustafa, Deborah Bard, Wahid Bhimji, Zarija Lukić, Rami Al-Rfou, and Jan M Kratochvil · 2019
Cited alongside, same era.
Nonlinear 3d cosmic web simulation with heavy-tailed generative adversarial networks
Richard M. Feder, Philippe Berger, and George Stein · 2020
Cited alongside, same era.
Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
Cited alongside, same era.
Quantimpy: Minkowski functionals and functions with python
Arnout MP Boelens and Hamdi A Tchelepi · 2021
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Building high accuracy emulators for scientific simulations with deep neural architecture search
MF Kasim, D Watson-Parris, L Deaconu, S Oliver, P Hatfield, DH Froula, G Gregori, M Jarvis, S Khatiwala, J Korenaga, et al · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Later among the works it cites.
Field level neural network emulator for cosmological n-body simulations
Drew Jamieson, Yin Li, Renan Alves de Oliveira, Francisco Villaescusa-Navarro, Shirley Ho, and David N Spergel · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, et al · 2022
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Probabilistic mapping of dark matter by neural score matching
Benjamin Rémy, Francois Lanusse, Zaccharie Ramzi, Jia Liu, Niall Jeffrey, and Jean-Luc Starck · 2020
Cited alongside, same era.
Experiment tracking with weights and biases, 2020
Lukas Biewald · 2020
Cited alongside, same era.
Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Cited alongside, same era.
The camels project: Cosmology and astrophysics with machine-learning simulations
Francisco Villaescusa-Navarro, Daniel Anglés-Alcázar, Shy Genel, David N Spergel, Rachel S Somerville, Romeel Dave, Annalisa Pillepich, Lars Hernquist, Dylan Nelson, Paul Torrey, et al · 2021
Cited alongside, same era.
Efficient attention: Attention with linear complexities
Zhuoran Shen, Mingyuan Zhang, Haiyu Zhao, Shuai Yi, and Hongsheng Li · 2021
Cited alongside, same era.
Investigating cosmological gan emulators using latent space interpolation
Andrius Tamosiunas, Hans A Winther, Kazuya Koyama, David J Bacon, Robert C Nichol, and Ben Mawdsley · 2021
Cited alongside, same era.
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Realistic galaxy image simulation via score-based generative models
Michael J Smith, James E Geach, Ryan A Jackson, Nikhil Arora, Connor Stone, and Stéphane Courteau · 2022
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Probabilistic mass mapping with neural score estimation
Benjamin Remy, Francois Lanusse, Niall Jeffrey, Jean-Luc Starck, Ken Osato, and Tim Schrabback · 2022
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The camels multifield data set: Learning the universe’s fundamental parameters with artificial intelligence
Francisco Villaescusa-Navarro, Shy Genel, Daniel Angles-Alcazar, Leander Thiele, Romeel Dave, Desika Narayanan, Andrina Nicola, Yin Li, Pablo Villanueva-Domingo, Benjamin Wandelt, et al · 2022
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The annotated diffusion model, 2022
Niels Rogge and Kashif Rasul · 2022
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Generative models of multi-channel data from a single example–application to dust emission
Bruno Régaldo-Saint Blancard, Erwan Allys, Constant Auclair, François Boulanger, Michael Eickenberg, François Levrier, Léo Vacher, and Sixin Zhang · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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