Fetching the paper…
Reading the bibliography…
Denoising diffusion models are a novel class of generative algorithms that achieve state-of-the-art performance across a range of domains, including image generation and text-to-image tasks.
Stochastic equations for diffusion processes in a bounded region
Anatoliy V Skorokhod · 1961
Earlier work this paper cites.
The central limit problem for geodesic random walks
Erik Jørgensen · 1975
Earlier work this paper cites.
Criteria for recurrence and existence of invariant measures for multidimensional diffusions
RN Bhattacharya · 1978
Earlier work this paper cites.
Stochastic differential equations with reflecting boundary conditions
Pierre-Louis Lions and Alain-Sol Sznitman · 1984
Earlier work this paper cites.
Efficient Monte Carlo Procedures for Generating Points Uniformly Distributed over Bounded Regions
Robert L. Smith · 1984
Earlier work this paper cites.
Manipulability of robotic mechanisms
Tsuneo Yoshikawa · 1985
Earlier work this paper cites.
Time reversal of diffusions
Ulrich G Haussmann and Etienne Pardoux · 1986
Earlier work this paper cites.
Brownian models of open queueing networks with homogeneous customer populations
J Michael Harrison and Ruth J Williams · 1987
Earlier work this paper cites.
Stability of markovian processes ii: Continuous-time processes and sampled chains
Sean P Meyn and Richard L Tweedie · 1993
Earlier work this paper cites.
Precise estimates on the rate at which certain diffusions tend to equilibrium
Laurent Saloff-Coste · 1994
Earlier work this paper cites.
Time reversal and reflected diffusions
Frédérique Petit · 1997
Earlier work this paper cites.
Geometry of hessian manifolds
Hirohiko Shima and Katsumi Yagi · 1997
Earlier work this paper cites.
Numerical approximation for functionals of reflecting diffusion processes
Barbara Pacchiarotti, Cristina Costantini, and Flavio Sartoretto · 1998
Earlier work this paper cites.
Stochastic analysis on manifolds
Elton P Hsu · 2002
Earlier work this paper cites.
Improved bounds for sampling contingency tables
Ben J. Morris · 2002
Earlier work this paper cites.
A symmetrized euler scheme for an efficient approximation of reflected diffusions
Mireille Bossy, Emmanuel Gobet, and Denis Talay · 2004
Earlier work this paper cites.
Convex optimization
Stephen Boyd, Stephen P Boyd, and Lieven Vandenberghe · 2004
Earlier work this paper cites.
The heat equation and reflected brownian motion in time-dependent domains
Krzysztof Burdzy, Zhen-Qing Chen, and John Sylvester · 2004
Earlier work this paper cites.
Estimation of non-normalized statistical models by score matching
Aapo Hyvärinen · 2005
Earlier work this paper cites.
Traps for reflected brownian motion
Krzysztof Burdzy, Zhen-Qing Chen, and Donald E Marshall · 2006
Earlier work this paper cites.
Inverse kinematics for a serial chain with joints under distance constraints
Li Han and Lee Rudolph · 2006
Earlier work this paper cites.
Comparison of multiple amber force fields and development of improved protein backbone parameters
Viktor Hornak, Robert Abel, Asim Okur, Bentley Strockbine, Adrian Roitberg, and Carlos Simmerling · 2006
Earlier work this paper cites.
Riemannian manifolds: an introduction to curvature , volume 176
John M Lee · 2006
Earlier work this paper cites.
Hit-and-run from a corner
László Lovász and Santosh Vempala · 2006
Earlier work this paper cites.
The Malliavin calculus and related topics , volume 1995
David Nualart · 2006
Earlier work this paper cites.
Fast procedure for reconstruction of full-atom protein models from reduced representations
Piotr Rotkiewicz and Jeffrey Skolnick · 2008
Cited alongside, same era.
Random walks on polytopes and an affine interior point method for linear programming
Ravi Kannan and Hariharan Narayanan · 2009
Cited alongside, same era.
A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
Cited alongside, same era.
Projection-like retractions on matrix manifolds
P-A Absil and Jérôme Malick · 2012
Cited alongside, same era.
A kernel two-sample test
Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, and Alexander Smola · 2012
Cited alongside, same era.
Matrix computations, 2013
Gene H Golub and Charles F Van Loan · 2013
Cited alongside, same era.
A practical and efficient approach for bayesian quantum state estimation
Joseph M Lukens, Kody JH Law, Ajay Jasra, and Pavel Lougovski · 2020
Later among the works it cites.
Geomstats: A python package for riemannian geometry in machine learning
Nina Miolane, Nicolas Guigui, Alice Le Brigant, Johan Mathe, Benjamin Hou, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Daniel Brooks, Bernhard Kainz, Claire Donnat, Susan Holmes, and Xavier Pennec · 2020
Later among the works it cites.
Time reversal of diffusion processes under a finite entropy condition
Patrick Cattiaux, Giovanni Conforti, Ivan Gentil, and Christian Léonard · 2021
Later among the works it cites.
A variational perspective on diffusion-based generative models and score matching
Chin-Wei Huang, Jae Hyun Lim, and Aaron C Courville · 2021
Later among the works it cites.
Geometry-aware manipulability learning, tracking, and transfer
Noémie Jaquier, Leonel Rozo, Darwin G Caldwell, and Sylvain Calinon · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Smooth manifolds
John M Lee · 2013
Cited alongside, same era.
Continuous martingales and Brownian motion , volume 293
Daniel Revuz and Marc Yor · 2013
Cited alongside, same era.
Time-reversal of reflected Brownian motions in the orthant, July 2013
Mykhaylo Shkolnikov and Ioannis Karatzas · 2013
Cited alongside, same era.
A community-driven global reconstruction of human metabolism
Ines Thiele, Neil Swainston, Ronan M T Fleming, Andreas Hoppe, Swagatika Sahoo, Maike K Aurich, Hulda Haraldsdottir, Monica L Mo, Ottar Rolfsson, Miranda D Stobbe, Stefan G Thorleifsson, Rasmus Agren, Christian Bölling, Sergio Bordel, Arvind K Chavali, Paul Dobson, Warwick B Dunn, Lukas Endler, David Hala, Michael Hucka, Duncan Hull, Daniel Jameson, Neema Jamshidi, Jon J Jonsson, Nick Juty, Sarah Keating, Intawat Nookaew, Nicolas Le Novère, Naglis Malys, Alexander Mazein, Jason A Papin, Nathan D Price, Evgeni Selkov, Martin I Sigurdsson, Evangelos Simeonidis, Nikolaus Sonnenschein, Kieran Smallbone, Anatoly Sorokin, Johannes H G M van Beek, Dieter Weichart, Igor Goryanin, Jens Nielsen, Hans V Westerhoff, Douglas B Kell, Pedro Mendes, and Bernhard Ø Palsson · 2013
Cited alongside, same era.
Stochastic differential equations and diffusion processes
Nobuyuki Ikeda and Shinzo Watanabe · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization, 2014
Diederik P. Kingma and Jimmy Ba · 2014
Cited alongside, same era.
Later among the works it cites.
Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
Later among the works it cites.
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking, October 2022
Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, and Tommi Jaakkola · 2022
Later among the works it cites.
Riemannian score-based generative modeling, 2022
Valentin De Bortoli, Emile Mathieu, Michael Hutchinson, James Thornton, Yee Whye Teh, and Arnaud Doucet · 2022
Later among the works it cites.
Convergence of the riemannian langevin algorithm
Khashayar Gatmiry and Santosh S Vempala · 2022
Later among the works it cites.
Riemannian Diffusion Models, August 2022
Chin-Wei Huang, Milad Aghajohari, Avishek Joey Bose, Prakash Panangaden, and Aaron Courville · 2022
Later among the works it cites.
Torsional Diffusion for Molecular Conformer Generation, June 2022
Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, and Tommi Jaakkola · 2022
Later among the works it cites.
Sampling with riemannian hamiltonian monte carlo in a constrained space
Yunbum Kook, Yin Tat Lee, Ruoqi Shen, and Santosh S Vempala · 2022
Later among the works it cites.
Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment
Adam Leach, Sebastian M Schmon, Matteo T Degiacomi, and Chris G Willcocks · 2022
Later among the works it cites.
Estimating density models with truncation boundaries using score matching
Song Liu, Takafumi Kanamori, and Daniel J Williams · 2022
Later among the works it cites.
Barrier Hamiltonian Monte Carlo, October 2022
Maxence Noble, Valentin De Bortoli, and Alain Durmus · 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 L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
Later among the works it cites.
Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem, June 2022
Brian L. Trippe, Jason Yim, Doug Tischer, Tamara Broderick, David Baker, Regina Barzilay, and Tommi Jaakkola · 2022
Later among the works it cites.
Julen Urain, Niklas Funk, Georgia Chalvatzaki, and Jan Peters · 2022
Later among the works it cites.
Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models, December 2022
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, Basile I. M. Wicky, Nikita Hanikel, Samuel J. Pellock, Alexis Courbet, William Sheffler, Jue Wang, Preetham Venkatesh, Isaac Sappington, Susana Vázquez Torres, Anna Lauko, Valentin De Bortoli, Emile Mathieu, Regina Barzilay, Tommi S. Jaakkola, Frank DiMaio, Minkyung Baek, and David Baker · 2022
Later among the works it cites.
Protein structure generation via folding diffusion
Kevin E Wu, Kevin K Yang, Rianne van den Berg, James Y Zou, Alex X Lu, and Ava P Amini · 2022
Later among the works it cites.
An introduction to optimization on smooth manifolds
Nicolas Boumal · 2023
Closest in time.
Protein structure prediction has reached the single-structure frontier
Thomas J Lane · 2023
Closest in time.
Aaron Lou and Stefano Ermon · 2023
Closest in time.
Se (3) diffusion model with application to protein backbone generation
Jason Yim, Brian L Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, and Tommi Jaakkola · 2023
Closest in time.
Reflected Brownian motion with skew symmetric data in a polyhedral domain
R. J. Williams · 2064
Closest in time.