Fetching the paper…
Reading the bibliography…
We introduce Functional Diffusion Processes (FDPs), which generalize score-based diffusion models to infinite-dimensional function spaces.
Communication in the presence of noise
C.E. Shannon · 1949
Earlier work this paper cites.
Reverse-time diffusion equation models
Brian D. O. Anderson · 1982
Earlier work this paper cites.
Some comments on fourier analysis, uncertainty and modeling
David Slepian · 1983
Earlier work this paper cites.
An entropy approach to the time reversal of diffusion processes
Hans Föllmer · 1985
Earlier work this paper cites.
Time reversal on wiener space
Hans Föllmer · 1986
Earlier work this paper cites.
Time reversal of infinite-dimensional diffusions
H. Föllmer and A. Wakolbinger · 1986
Earlier work this paper cites.
Time reversal for infinite-dimensional diffusions
Annie Millet, David Nualart, and Marta Sanz · 1989
Earlier work this paper cites.
Lattice approximations for stochastic quasi-linear parabolic partial differential equations driven by space-time white noise i
István Gyöngy · 1998
Earlier work this paper cites.
Lattice approximations for stochastic quasi-linear parabolic partial differential equations driven by space-time white noise ii
István Gyöngy · 1999
Earlier work this paper cites.
Numerical methods for stochastic parabolic pdes
Tony Shardlow · 1999
Earlier work this paper cites.
A sampling theorem on homogeneous manifolds
Isaac Pesenson · 2000
Earlier work this paper cites.
Semi-discretization of stochastic partial differential equations on r by a finite-difference method
Hyek Yoo · 2000
Earlier work this paper cites.
Existence and uniqueness of solutions for fokker-planck equations on hilbert spaces
Vladimir Bogachev, Giuseppe Da Prato, and Michael Röckner · 2009
Earlier work this paper cites.
Mnist handwritten digit database
Yann LeCun, Corinna Cortes, and CJ Burges · 2010
Earlier work this paper cites.
Uniqueness for solutions of fokker–planck equations on infinite dimensional spaces
Vladimir Bogachev, Giuseppe Da Prato, and Michael Röckner · 2011
Earlier work this paper cites.
Weak approximation of stochastic partial differential equations: the nonlinear case
Arnaud Debussche · 2011
Earlier work this paper cites.
A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
Earlier work this paper cites.
Stochastic equations in infinite dimensions
Giuseppe Da Prato and Jerzy Zabczyk · 2014
Earlier work this paper cites.
Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
Earlier work this paper cites.
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
Earlier work this paper cites.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Jax: composable transformations of python+ numpy programs
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, et al · 2018
Cited alongside, same era.
Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
Cited alongside, same era.
Experiment tracking with weights and biases, 2020
Lukas Biewald · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Fourier neural operator for parametric partial differential equations
Latent video diffusion models for high-fidelity video generation with arbitrary lengths
Yingqing He, Tianyu Yang, Yong Zhang, Ying Shan, and Qifeng Chen · 2022
Later among the works it cites.
Imagen video: High definition video generation with diffusion models, 2022
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey Gritsenko, Diederik P. Kingma, Ben Poole, Mohammad Norouzi, David J. Fleet, and Tim Salimans · 2022
Later among the works it cites.
Equivariant diffusion for molecule generation in 3D
Emiel Hoogeboom, Víctor Garcia Satorras, Clément Vignac, and Max Welling · 2022
Later among the works it cites.
Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, and Anima Anandkumar · 2020
Cited alongside, same era.
Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien Martel, Alexander Bergman, David Lindell, and Gordon Wetzstein · 2020
Cited alongside, same era.
Improved techniques for training score-based generative models
Yang Song and Stefano Ermon · 2020
Cited alongside, same era.
Adabelief optimizer: Adapting stepsizes by the belief in observed gradients
Juntang Zhuang, Tommy Tang, Yifan Ding, Sekhar C Tatikonda, Nicha Dvornek, Xenophon Papademetris, and James Duncan · 2020
Cited alongside, same era.
Choose a transformer: Fourier or galerkin
Shuhao Cao · 2021
Cited alongside, same era.
Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Cited alongside, same era.
Cascaded diffusion models for high fidelity image generation, 2021
Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, and Tim Salimans · 2021
Cited alongside, same era.
Gavin Kerrigan, Justin Ley, and Padhraic Smyth · 2022
Later among the works it cites.
The role of imagenet classes in fréchet inception distance
Tuomas Kynkäänniemi, Tero Karras, Miika Aittala, Timo Aila, and Jaakko Lehtinen · 2022
Later among the works it cites.
Diffsinger: Singing voice synthesis via shallow diffusion mechanism
Jinglin Liu, Chengxi Li, Yi Ren, Feiyang Chen, and Zhou Zhao · 2022
Later among the works it cites.
From points to functions: Infinite-dimensional representations in diffusion models
Sarthak Mittal, Guillaume Lajoie, Stefan Bauer, and Arash Mehrjou · 2022
Later among the works it cites.
Angus Phillips, Thomas Seror, Michael Hutchinson, Valentin De Bortoli, Arnaud Doucet, and Emile Mathieu · 2022
Later among the works it cites.
Hierarchical text-conditional image generation with clip latents, 2022
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Later among the works it cites.
Generative modelling with inverse heat dissipation
Severi Rissanen, Markus Heinonen, and Arno Solin · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Later among the works it cites.
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, Raphael Gontijo-Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J. Fleet, and Mohammad Norouzi · 2022
Later among the works it cites.
Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
Later among the works it cites.
Diffusion probabilistic modeling of protein backbones in 3d for the motif-scaffolding problem, 2022
Brian L. Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, and Tommi Jaakkola · 2022
Later among the works it cites.
Tackling the generative learning trilemma with denoising diffusion GANs
Zhisheng Xiao, Karsten Kreis, and Arash Vahdat · 2022
Later among the works it cites.
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
Later among the works it cites.
∞ \infty -diff: Infinite resolution diffusion with subsampled mollified states
Sam Bond-Taylor and Chris G Willcocks · 2023
Closest in time.
Multilevel diffusion: Infinite dimensional score-based diffusion models for image generation, 2023
Paul Hagemann, Sophie Mildenberger, Lars Ruthotto, Gabriele Steidl, and Nicole Tianjiao Yang · 2023
Closest in time.
Score-based diffusion models in function space
Jae Hyun Lim, Nikola B Kovachki, Ricardo Baptista, Christopher Beckham, Kamyar Azizzadenesheli, Jean Kossaifi, Vikram Voleti, Jiaming Song, Karsten Kreis, Jan Kautz, et al · 2023
Closest in time.
Infinite-dimensional diffusion models for function spaces
Jakiw Pidstrigach, Youssef Marzouk, Sebastian Reich, and Sven Wang · 2023
Closest in time.
Wire: Wavelet implicit neural representations
Vishwanath Saragadam, Daniel LeJeune, Jasper Tan, Guha Balakrishnan, Ashok Veeraraghavan, and Richard G Baraniuk · 2023
Closest in time.
Diffusion probabilistic fields
Peiye Zhuang, Samira Abnar, Jiatao Gu, Alex Schwing, Joshua M. Susskind, and Miguel Ángel Bautista · 2023
Closest in time.