Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions

14 February 2023

Papers citing "Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions"

20 / 20 papers shown

Title
SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations Grigory Bartosh Dmitry Vetrov C. A. Naesseth 76 0 0 04 Feb 2025
Weak Supervision Dynamic KL-Weighted Diffusion Models Guided by Large Language Models Julian Perry Frank Sanders Carter Scott 53 0 0 02 Feb 2025
A General Framework for Inference-time Scaling and Steering of Diffusion Models R. Singhal Zachary Horvitz Ryan Teehan Mengye Ren Zhou Yu Kathleen McKeown Rajesh Ranganath DiffM 61 15 0 17 Jan 2025
Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities A. Saporta A. Puli Mark Goldstein Rajesh Ranganath SSL 23 0 0 01 Nov 2024
What's the score? Automated Denoising Score Matching for Nonlinear Diffusions Raghav Singhal Mark Goldstein Rajesh Ranganath DiffM 43 4 0 10 Jul 2024
Variational Flow Matching for Graph Generation Floor Eijkelboom Grigory Bartosh C. A. Naesseth Max Welling Jan Willem van de Meent 31 10 0 07 Jun 2024
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling Grigory Bartosh Dmitry Vetrov C. A. Naesseth DiffM 29 7 0 19 Apr 2024
On the Challenges and Opportunities in Generative AI Laura Manduchi Kushagra Pandey Robert Bamler Ryan Cotterell Sina Daubener ... F. Wenzel Frank Wood Stephan Mandt Vincent Fortuin Vincent Fortuin 56 17 0 28 Feb 2024
Structure-Guided Adversarial Training of Diffusion Models Ling Yang Haotian Qian Zhilong Zhang Jingwei Liu Bin Cui 23 10 0 27 Feb 2024
Towards Fast Stochastic Sampling in Diffusion Generative Models Kushagra Pandey Maja R. Rudolph Stephan Mandt DiffM 25 0 0 11 Feb 2024
SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers Nanye Ma Mark Goldstein M. S. Albergo Nicholas M. Boffi Eric Vanden-Eijnden Saining Xie DiffM 27 163 0 16 Jan 2024
DiffEnc: Variational Diffusion with a Learned Encoder Beatrix M. G. Nielsen Anders Christensen Andrea Dittadi Ole Winther DiffM 11 9 0 30 Oct 2023
Generative Fractional Diffusion Models Gabriel Nobis Maximilian Springenberg Marco Aversa Michael Detzel Rembert Daems ... Tolga Birdal Manfred Opper Christoph Knochenhauer Luis Oala Wojciech Samek DiffM 24 5 0 26 Oct 2023
Neural Diffusion Models Grigory Bartosh Dmitry Vetrov C. A. Naesseth DiffM 24 6 0 12 Oct 2023
Efficient Integrators for Diffusion Generative Models Kushagra Pandey Maja R. Rudolph Stephan Mandt DiffM 21 10 0 11 Oct 2023
Stochastic interpolants with data-dependent couplings M. S. Albergo Mark Goldstein Nicholas M. Boffi Rajesh Ranganath Eric Vanden-Eijnden OT 30 28 0 05 Oct 2023
Learning variational autoencoders via MCMC speed measures Marcel Hirt Vasileios Kreouzis P. Dellaportas BDL DRL 13 2 0 26 Aug 2023
Protein Design with Guided Discrete Diffusion Nate Gruver Samuel Stanton Nathan C. Frey Tim G. J. Rudner I. Hotzel J. Lafrance-Vanasse A. Rajpal Kyunghyun Cho A. Wilson DiffM 24 100 0 31 May 2023
A Complete Recipe for Diffusion Generative Models Kushagra Pandey Stephan Mandt DiffM 41 8 0 03 Mar 2023
A Continuous Time Framework for Discrete Denoising Models Andrew Campbell Joe Benton Valentin De Bortoli Tom Rainforth George Deligiannidis Arnaud Doucet DiffM 183 134 0 30 May 2022