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Given an unconditional diffusion model and a predictor for a target property of interest (e.g., a classifier), the goal of training-free guidance is to generate samples with desirable target properties without additional training.
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A tutorial on energy-based learning
Yann LeCun, Sumit Chopra, Raia Hadsell, M Ranzato, and Fujie Huang · 2006
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Asirra: A captcha that exploits interest-aligned manual image categorization
Jeremy Elson, John (JD) Douceur, Jon Howell, and Jared Saul · 2007
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Understanding and evaluating blind deconvolution algorithms
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Ornstein–uhlenbeck processes and extensions
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Tweedie’s formula and selection bias
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Super-resolution: a comprehensive survey
Kamal Nasrollahi and Thomas B Moeslund · 2014
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Quantum chemistry structures and properties of 134 kilo molecules
Raghunathan Ramakrishnan, Pavlo O Dral, Matthias Rupp, and O Anatole von Lilienfeld · 2014
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Part-based r-cnns for fine-grained category detection
Ning Zhang, Jeff Donahue, Ross Girshick, and Trevor Darrell · 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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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Large-scale classification of fine-art paintings: Learning the right metric on the right feature
Babak Saleh and Ahmed Elgammal · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
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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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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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Mikołaj Bińkowski, Danica J Sutherland, Michael Arbel, and Arthur Gretton · 2018
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Fr \ \backslash ’echet audio distance: A metric for evaluating music enhancement algorithms
Kevin Kilgour, Mauricio Zuluaga, Dominik Roblek, and Matthew Sharifi · 2018
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Large-scale celebfaces attributes (celeba) dataset
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Diffwave: A versatile diffusion model for audio synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
Openood: Benchmarking generalized out-of-distribution detection
Jingkang Yang, Pengyun Wang, Dejian Zou, Zitang Zhou, Kunyuan Ding, Wenxuan Peng, Haoqi Wang, Guangyao Chen, Bo Li, Yiyou Sun, Xuefeng Du, Kaiyang Zhou, Wayne Zhang, Dan Hendrycks, Yixuan Li, and Ziwei Liu · 2022
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Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, et al · 2022
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Universal guidance for diffusion models
Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, and Tom Goldstein · 2023
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Equivariant energy-guided SDE for inverse molecular design
Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, and Jun Zhu · 2023
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Reduce, reuse, recycle: Compositional generation with energy-based diffusion models and mcmc
Yilun Du, Conor Durkan, Robin Strudel, Joshua B Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, and Will Sussman Grathwohl · 2023
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Deep learning for image super-resolution: A survey
Zhihao Wang, Jian Chen, and Steven CH Hoi · 2020
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Conditional image generation with score-based diffusion models
Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, and Christian Etmann · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Diffusion probabilistic models for 3d point cloud generation
Shitong Luo and Wei Hu · 2021
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A conditional point diffusion-refinement paradigm for 3d point cloud completion
Zhaoyang Lyu, Zhifeng Kong, Xudong Xu, Liang Pan, and Dahua Lin · 2021
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2021
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Conditional generation from unconditional diffusion models using denoiser representations
Alexandros Graikos, Srikar Yellapragada, and Dimitris Samaras · 2023
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Training-free multi-objective diffusion model for 3d molecule generation
Xu Han, Caihua Shan, Yifei Shen, Can Xu, Han Yang, Xiang Li, and Dongsheng Li · 2023
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Controllable music production with diffusion models and guidance gradients
Mark Levy, Bruno Di Giorgi, Floris Weers, Angelos Katharopoulos, and Tom Nickson · 2023
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Audioldm: Text-to-audio generation with latent diffusion models
Haohe Liu, Zehua Chen, Yi Yuan, Xinhao Mei, Xubo Liu, Danilo Mandic, Wenwu Wang, and Mark D Plumbley · 2023
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Contrastive energy prediction for exact energy-guided diffusion sampling in offline reinforcement learning
Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, and Jun Zhu · 2023
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Solving audio inverse problems with a diffusion model
Eloi Moliner, Jaakko Lehtinen, and Vesa Välimäki · 2023
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Steered diffusion: A generalized framework for plug-and-play conditional image synthesis
Nithin Gopalakrishnan Nair, Anoop Cherian, Suhas Lohit, Ye Wang, Toshiaki Koike-Akino, Vishal M Patel, and Tim K Marks · 2023
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Loss-guided diffusion models for plug-and-play controllable generation
Jiaming Song, Qinsheng Zhang, Hongxu Yin, Morteza Mardani, Ming-Yu Liu, Jan Kautz, Yongxin Chen, and Arash Vahdat · 2023
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Zero-shot image restoration using denoising diffusion null-space model
Yinhuai Wang, Jiwen Yu, and Jian Zhang · 2023
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De novo design of protein structure and function with rfdiffusion
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, et al · 2023
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Geometric latent diffusion models for 3d molecule generation
Minkai Xu, Alexander S Powers, Ron O Dror, Stefano Ermon, and Jure Leskovec · 2023
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Freeze then train: Towards provable representation learning under spurious correlations and feature noise
Haotian Ye, James Zou, and Linjun Zhang · 2023
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Freedom: Training-free energy-guided conditional diffusion model
Jiwen Yu, Yinhuai Wang, Chen Zhao, Bernard Ghanem, and Jian Zhang · 2023
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Accurate structure prediction of biomolecular interactions with alphafold 3
Josh Abramson, Jonas Adler, Jack Dunger, Richard Evans, Tim Green, Alexander Pritzel, Olaf Ronneberger, Lindsay Willmore, Andrew J Ballard, Joshua Bambrick, et al · 2024
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A framework for conditional diffusion modelling with applications in motif scaffolding for protein design, 2024
Kieran Didi, Francisco Vargas, Simon V Mathis, Vincent Dutordoir, Emile Mathieu, Urszula J Komorowska, and Pietro Lio · 2024
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Motion guidance: Diffusion-based image editing with differentiable motion estimators
Daniel Geng and Andrew Owens · 2024
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Control3diff: Learning controllable 3d diffusion models from single-view images
Jiatao Gu, Qingzhe Gao, Shuangfei Zhai, Baoquan Chen, Lingjie Liu, and Josh Susskind · 2024
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Manifold preserving guided diffusion
Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J Zico Kolter, Ruslan Salakhutdinov, and Stefano Ermon · 2024
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Vrdmg: Vocal restoration via diffusion posterior sampling with multiple guidance
Carlos Hernandez-Olivan, Koichi Saito, Naoki Murata, Chieh-Hsin Lai, Marco A Martínez-Ramirez, Wei-Hsiang Liao, and Yuki Mitsufuji · 2024
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Diffusion models for audio restoration
Jean-Marie Lemercier, Julius Richter, Simon Welker, Eloi Moliner, Vesa Välimäki, and Timo Gerkmann · 2024
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Haoyuan Sun, Bo Xia, Yongzhe Chang, and Xueqian Wang · 2024
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