Implicit Diffusion: Efficient Optimization through Stochastic Sampling

Implicit Diffusion: Efficient Optimization through Stochastic Sampling

8 February 2024

Mathieu Blondel

Valentin De Bortoli

Felipe Llinares-López

Courtney Paquette

Quentin Berthet

Papers citing "Implicit Diffusion: Efficient Optimization through Stochastic Sampling"

19 / 19 papers shown

Title
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows Jonathan Geuter Clément Bonet Anna Korba David Alvarez-Melis 61 0 0 03 Mar 2025
Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods Oussama Zekri Nicolas Boullé DiffM 68 3 0 03 Feb 2025
Bayesian Experimental Design via Contrastive Diffusions Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 30 0 0 15 Oct 2024
Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics Omar Chehab Anna Korba Austin Stromme Adrien Vacher 35 2 0 13 Oct 2024
Attention layers provably solve single-location regression P. Marion Raphael Berthier Gérard Biau Claire Boyer 140 2 0 02 Oct 2024
ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization L. Eyring Shyamgopal Karthik Karsten Roth Alexey Dosovitskiy Zeynep Akata 78 17 0 06 Jun 2024
AdjointDEIS: Efficient Gradients for Diffusion Models Zander Blasingame Chen Liu DiffM 49 2 0 23 May 2024
Gradient Guidance for Diffusion Models: An Optimization Perspective Yingqing Guo Hui Yuan Yukang Yang Minshuo Chen Mengdi Wang 27 20 0 23 Apr 2024
Functional Bilevel Optimization for Machine Learning Ieva Petrulionyte Julien Mairal Michael Arbel 51 2 0 29 Mar 2024
Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control Masatoshi Uehara Yulai Zhao Kevin Black Ehsan Hajiramezanali Gabriele Scalia N. Diamant Alex Tseng Tommaso Biancalani Sergey Levine 42 42 0 23 Feb 2024
One-step differentiation of iterative algorithms Jérôme Bolte Edouard Pauwels Samuel Vaiter 69 13 0 23 May 2023
End-to-End Diffusion Latent Optimization Improves Classifier Guidance Bram Wallace Akash Gokul Stefano Ermon Nikhil Naik 124 70 0 23 Mar 2023
A Forward Propagation Algorithm for Online Optimization of Nonlinear Stochastic Differential Equations Ziheng Wang Justin A. Sirignano 64 3 0 10 Jul 2022
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms Mathieu Dagréou Pierre Ablin Samuel Vaiter Thomas Moreau 139 96 0 31 Jan 2022
Amortized Implicit Differentiation for Stochastic Bilevel Optimization Michael Arbel Julien Mairal 105 58 0 29 Nov 2021
Fine-Tuning Language Models from Human Preferences Daniel M. Ziegler Nisan Stiennon Jeff Wu Tom B. Brown Alec Radford Dario Amodei Paul Christiano G. Irving ALM 280 1,595 0 18 Sep 2019
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 110 716 0 13 Jun 2018
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 321 75,834 0 18 May 2015
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 84 736 0 19 Mar 2014