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Accelerating Score-based Generative Models for High-Resolution Image SynthesisHengyuan Ma, Li Zhang, Xiatian Zhu, Jingfeng Zhang, Jianfeng FengarXiv 2022. Paper  2022-06-082022-06-08
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Diffusion-GAN: Training GANs with DiffusionZhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan ZhouarXiv 2022. Paper  2022-06-052022-06-05
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DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 StepsCheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun ZhuarXiv 2022. Paper  2022-06-022022-06-02
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Elucidating the Design Space of Diffusion-Based Generative ModelsTero Karras, Miika Aittala, Timo Aila, Samuli LainearXiv 2022. Paper  2022-06-012022-06-01
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On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative ModelsKamil Deja, Anna Kuzina, Tomasz Trzciński, Jakub M. TomczakarXiv 2022. Paper  2022-05-312022-05-31
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A Continuous Time Framework for Discrete Denoising ModelsAndrew Campbell, Joe Benton, Valentin De Bortoli, Tom Rainforth, George Deligiannidis, Arnaud DoucetarXiv 2022. Paper  2022-05-302022-05-30
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Few-Shot Diffusion ModelsGiorgio Giannone, Didrik Nielsen, Ole WintherarXiv 2022. Paper  2022-05-302022-05-30
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Maximum Likelihood Training of Implicit Nonlinear Diffusion ModelsDongjun Kim, Byeonghu Na, Se Jung Kwon, Dongsoo Lee, Wanmo Kang, Il-Chul MoonarXiv 2022. Paper  2022-05-272022-05-27
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Accelerating Diffusion Models via Early Stop of the Diffusion ProcessZhaoyang Lyu, Xudong XU, Ceyuan Yang, Dahua Lin, Bo DaiICML 2022. Paper  2022-05-252022-05-25
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On Conditioning the Input Noise for Controlled Image Generation with Diffusion ModelsVedant Singh1, Surgan Jandial1, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanianarxiv 2022. Paper  2022-05-082022-05-08
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Subspace Diffusion Generative ModelsBowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi Jaakkola2022-05-032022-05-03
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Fast Sampling of Diffusion Models with Exponential IntegratorQinsheng Zhang, Yongxin ChenarXiv 2022. Paper  2022-04-292022-04-29
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Retrieval-Augmented Diffusion ModelsAndreas Blattmann1, Robin Rombach1, Kaan Oktay, Björn OmmerarXiv 2022. Paper  2022-04-252022-04-25
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Perception Prioritized Training of Diffusion ModelsJooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim, Sungroh Yoon2022-04-012022-04-01
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Generating High Fidelity Data from Low-density Regions using Diffusion ModelsVikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton FerrerarXiv 2022. Paper  2022-03-312022-03-31
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Diffusion Models for Counterfactual ExplanationsGuillaume Jeanneret, Loïc Simon, Frédéric JuriearXiv 2022. Paper  2022-03-292022-03-29
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Denoising Likelihood Score Matching for Conditional Score-based Data GenerationChen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Yi-Chen Lo, Chia-Che Chang, Yu-Lun Liu, Yu-Lin Chang, Chia-Ping Chen, Chun-Yi LeeICLR 2022. Paper  2022-03-272022-03-27
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2022-03-08
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Conditional Simulation Using Diffusion Schrödinger BridgesYuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud DoucetarXiv 2022. Paper  2022-02-272022-02-27
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Diffusion Causal Models for Counterfactual EstimationPedro Sanchez, Sotirios A. TsaftarisPMLR 2022. Paper  2022-02-212022-02-21
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Pseudo Numerical Methods for Diffusion Models on ManifoldsLuping Liu, Yi Ren, Zhijie Lin, Zhou Zhao2022-02-202022-02-20
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Truncated Diffusion Probabilistic ModelsHuangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan ZhouarXiv 2022. Paper  2022-02-192022-02-19
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Understanding DDPM Latent Codes Through Optimal TransportValentin Khrulkov, Ivan OseledetsarXiv 2022. Paper  2022-02-142022-02-14
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Learning Fast Samplers for Diffusion Models by Differentiating Through Sample QualityDaniel Watson, William Chan, Jonathan Ho, Mohammad NorouziICLR 2022. Paper  2022-02-112022-02-11
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Progressive Distillation for Fast Sampling of Diffusion ModelsTim Salimans, Jonathan HoICLR 2022. Paper  2022-02-012022-02-01
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Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic ModelsFan Bao, Chongxuan Li, Jun Zhu, Bo ZhangarXiv 2022. Paper  2022-01-172022-01-17
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DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional LatentsKushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar2022-01-022022-01-02
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Diffusion Autoencoders: Toward a Meaningful and Decodable RepresentationKonpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, Supasorn Suwajanakorn2021-12-302021-12-30
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Itô-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models using Ideal DerivativesHideyuki Tachibana, Mocho Go, Muneyoshi Inahara, Yotaro Katayama, Yotaro WatanabearXiv 2021. Paper  2021-12-262021-12-26
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High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach1, Andreas Blattmann1, Dominik Lorenz, Patrick Esser, Björn Ommer2021-12-202021-12-20
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GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion ModelsAlex Nichol1, Prafulla Dhariwal1, Aditya Ramesh1, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark ChenarXiv 2021. Paper  2021-12-202021-12-20
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Heavy-tailed denoising score matchingJacob Deasy, Nikola Simidjievski, Pietro LiòarXiv 2021. Paper  2021-12-172021-12-17
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High Fidelity Visualization of What Your Self-Supervised Representation Knows AboutFlorian Bordes, Randall Balestriero, Pascal VincentarXiv 2021. Paper  2021-12-162021-12-16
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Tackling the Generative Learning Trilemma with Denoising Diffusion GANsZhisheng Xiao, Karsten Kreis, Arash Vahdat2021-12-152021-12-15
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Score-Based Generative Modeling with Critically-Damped Langevin DiffusionTim Dockhorn, Arash Vahdat, Karsten Kreis2021-12-142021-12-14
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More Control for Free! Image Synthesis with Semantic Diffusion GuidanceXihui Liu, Dong Huk Park, Samaneh Azadi, Gong Zhang, Arman Chopikyan, Yuxiao Hu, Humphrey Shi, Anna Rohrbach, Trevor DarrellarXiv 2021. Paper  2021-12-102021-12-10
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Global Context with Discrete Diffusion in Vector Quantised Modelling for Image GenerationMinghui Hu, Yujie Wang, Tat-Jen Cham, Jianfei Yang, P.N.SuganthanarXiv 2021. Paper  2021-12-032021-12-03
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Conditional Image Generation with Score-Based Diffusion ModelsGeorgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian EtmannarXiv 2021. Paper  2021-11-262021-11-26
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Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized CodesSam Bond-Taylor1, Peter Hessey1, Hiroshi Sasaki, Toby P. Breckon, Chris G. Willcocks2021-11-242021-11-24
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Diffusion Normalizing FlowQinsheng Zhang, Yongxin Chen2021-10-142021-10-14
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Denoising Diffusion Gamma ModelsEliya Nachmani1, Robin San Roman1, Lior WolfarXiv 2021. Paper  2021-10-102021-10-10
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Score-based Generative Neural Networks for Large-Scale Optimal TransportMax Daniels, Tyler Maunu, Paul HandarXiv 2021. Paper  2021-10-072021-10-07
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Score-Based Generative ClassifiersRoland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. KlindtarXiv 2021. Paper  2021-10-012021-10-01
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Bilateral Denoising Diffusion ModelsMax W. Y. Lam, Jun Wang, Rongjie Huang, Dan Su, Dong Yu2021-08-262021-08-26
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ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image SynthesisPatrick Esser1, Robin Rombach1, Andreas Blattmann1, Björn Ommer2021-08-192021-08-19
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ILVR: Conditioning Method for Denoising Diffusion Probabilistic ModelsJooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, Sungroh Yoon2021-08-062021-08-06
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SDEdit: Image Synthesis and Editing with Stochastic Differential EquationsChenlin Meng, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon2021-08-022021-08-02
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Structured Denoising Diffusion Models in Discrete State-SpacesJacob Austin1, Daniel D. Johnson1, Jonathan Ho, Daniel Tarlow, Rianne van den BergarXiv 2021. Paper  2021-07-072021-07-07
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Variational Diffusion ModelsDiederik P. Kingma1, Tim Salimans1, Ben Poole, Jonathan Ho2021-07-012021-07-01
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Deep Generative Learning via Schrödinger BridgeGefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can YangICML 2021. Paper  2021-06-192021-06-19
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Non Gaussian Denoising Diffusion ModelsEliya Nachmani1, Robin San Roman1, Lior Wolf2021-06-142021-06-14
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D2C: Diffusion-Denoising Models for Few-shot Conditional GenerationAbhishek Sinha1, Jiaming Song1, Chenlin Meng, Stefano Ermon2021-06-122021-06-12
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Score-based Generative Modeling in Latent SpaceArash Vahdat1, Karsten Kreis1, Jan KautzarXiv 2021. Paper  2021-06-102021-06-10
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Learning to Efficiently Sample from Diffusion Probabilistic ModelsDaniel Watson, Jonathan Ho, Mohammad Norouzi, William ChanarXiv 2021. Paper  2021-06-072021-06-07
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A Variational Perspective on Diffusion-Based Generative Models and Score MatchingChin-Wei Huang, Jae Hyun Lim, Aaron Courville2021-06-052021-06-05
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Diffusion Schrödinger Bridge with Applications to Score-Based Generative ModelingValentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet2021-06-012021-06-01
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On Fast Sampling of Diffusion Probabilistic ModelsZhifeng Kong, Wei Ping2021-05-312021-05-31
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Cascaded Diffusion Models for High Fidelity Image GenerationJonathan Ho1, Chitwan Saharia1, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans2021-05-302021-05-30
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Gotta Go Fast When Generating Data with Score-Based ModelsAlexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer, Tal Kachman, Ioannis Mitliagkas2021-05-282021-05-28
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Diffusion Models Beat GANs on Image SynthesisPrafulla Dhariwal1, Alex Nichol12021-05-112021-05-11
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Image Super-Resolution via Iterative RefinementChitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi2021-04-152021-04-15
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Noise Estimation for Generative Diffusion ModelsRobin San-Roman1, Eliya Nachmani1, Lior WolfarXiv 2021. Paper  2021-04-062021-04-06
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Improved Denoising Diffusion Probabilistic ModelsAlex Nichol1, Prafulla Dhariwal12021-02-182021-02-18
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Maximum Likelihood Training of Score-Based Diffusion ModelsYang Song1, Conor Durkan1, Iain Murray, Stefano ErmonarXiv 2021. Paper  2021-01-222021-01-22
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Learning Energy-Based Models by Diffusion Recovery LikelihoodRuiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma2020-12-152020-12-15
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Score-Based Generative Modeling through Stochastic Differential EquationsYang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole2020-11-262020-11-26
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Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable ModelsFan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo ZhangICML 2021. Paper  2020-10-162020-10-16
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Denoising Diffusion Implicit Models*Jiaming Song, Chenlin Meng, Stefano Ermon2020-10-062020-10-06
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Adversarial score matching and improved sampling for image generationAlexia Jolicoeur-Martineau1, Rémi Piché-Taillefer1, Rémi Tachet des Combes, Ioannis Mitliagkas2020-09-112020-09-11
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Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter Abbeel2020-06-192020-06-19
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Improved Techniques for Training Score-Based Generative ModelsYang Song, Stefano Ermon2020-06-162020-06-16
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Generative Modeling by Estimating Gradients of the Data DistributionYang Song, Stefano Ermon2019-07-122019-07-12
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Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion LimitBelinda Tzen, Maxim RaginskyarXiv 2019. Paper  2019-05-232019-05-23
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Deep Unsupervised Learning using Nonequilibrium ThermodynamicsJascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, Surya Ganguli2015-03-022015-03-02
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