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Bayesian flow networks (BFNs) iteratively refine the parameters, instead of the samples in diffusion models (DMs), of distributions at various noise levels through Bayesian inference.
Reverse-time diffusion equation models
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Stochastic differential equations
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Stochastic differential equations
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Estimation of non-normalized statistical models by score matching
Hyvärinen, A · 2005
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Numerical solution of ordinary differential equations , volume 81
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Learning multiple layers of features from tiny images
Krizhevsky, A. and Hinton, G · 2009
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A connection between score matching and denoising autoencoders
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Deep unsupervised learning using nonequilibrium thermodynamics
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
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Sliced score matching: A scalable approach to density and score estimation
Song, Y., Garg, S., Shi, J., and Ermon, S · 2019
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Language models are few-shot learners
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Wavegrad: Estimating gradients for waveform generation
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Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
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Diffwave: A versatile diffusion model for audio synthesis
Kong, Z., Ping, W., Huang, J., Zhao, K., and Catanzaro, B · 2020
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Efficient learning of generative models via finite-difference score matching
Pang, T., Xu, K., Li, C., Song, Y., Ermon, S., and Zhu, J · 2020
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Swapping autoencoder for deep image manipulation
Park, T., Zhu, J.-Y., Wang, O., Lu, J., Shechtman, E., Efros, A., and Zhang, R · 2020
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Denoising diffusion implicit models
Song, J., Meng, C., and Ermon, S · 2020
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Diffusion models beat gans on image synthesis
Dhariwal, P. and Nichol, A · 2021
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Argmax flows and multinomial diffusion: Learning categorical distributions, 2021
Hoogeboom, E., Nielsen, D., Jaini, P., Forré, P., and Welling, M · 2021
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Gotta go fast when generating data with score-based models
Jolicoeur-Martineau, A., Li, K., Piché-Taillefer, R., Kachman, T., and Mitliagkas, I · 2021
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Variational diffusion models
Kingma, D., Salimans, T., Poole, B., and Ho, J · 2021
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Score-based generative modeling through stochastic differential equations, 2021
Song, Y., Sohl-Dickstein, J., Kingma, D. P., Kumar, A., Ermon, S., and Poole, B · 2021
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Text2live: Text-driven layered image and video editing
Bar-Tal, O., Ofri-Amar, D., Fridman, R., Kasten, Y., and Dekel, T · 2022
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Make-a-video: Text-to-video generation without text-video data
Singer, U., Polyak, A., Hayes, T., Yin, X., An, J., Zhang, S., Hu, Q., Yang, H., Ashual, O., Gafni, O., et al · 2022
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gddim: Generalized denoising diffusion implicit models
Zhang, Q., Tao, M., and Chen, Y · 2022
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Structured denoising diffusion models in discrete state-spaces, 2023
Austin, J., Johnson, D. D., Ho, J., Tarlow, D., and van den Berg, R · 2023
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ediff-i: Text-to-image diffusion models with an ensemble of expert denoisers, 2023
Balaji, Y., Nah, S., Huang, X., Vahdat, A., Song, J., Zhang, Q., Kreis, K., Aittala, M., Aila, T., Laine, S., Catanzaro, B., Karras, T., and Liu, M.-Y · 2023
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One transformer fits all distributions in multi-modal diffusion at scale
Bao, F., Nie, S., Xue, K., Li, C., Pu, S., Wang, Y., Yue, G., Cao, Y., Su, H., and Zhu, J · 2023
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Campbell, A., Benton, J., Bortoli, V. D., Rainforth, T., Deligiannidis, G., and Doucet, A · 2022
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Dieleman, S., Sartran, L., Roshannai, A., Savinov, N., Ganin, Y., Richemond, P. H., Doucet, A., Strudel, R., Dyer, C., Durkan, C., Hawthorne, C., Leblond, R., Grathwohl, W., and Adler, J · 2022
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Imagen video: High definition video generation with diffusion models
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Autoregressive diffusion models
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Elucidating the design space of diffusion-based generative models
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Bayesian flow networks, 2023
Graves, A., Srivastava, R. K., Atkinson, T., and Gomez, F · 2023
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Gaussian mixture solvers for diffusion models
Guo, H., Lu, C., Bao, F., Pang, T., Yan, S., Du, C., and Li, C · 2023
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Imagic: Text-based real image editing with diffusion models
Kawar, B., Zada, S., Lang, O., Tov, O., Chang, H., Dekel, T., Mosseri, I., and Irani, M · 2023
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Lou, A. and Ermon, S · 2023
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Discrete diffusion language modeling by estimating the ratios of the data distribution, 2023
Lou, A., Meng, C., and Ermon, S · 2023
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Tess: Text-to-text self-conditioned simplex diffusion
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Concrete score matching: Generalized score matching for discrete data, 2023
Meng, C., Choi, K., Song, J., and Ermon, S · 2023
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The blessing of randomness: Sde beats ode in general diffusion-based image editing
Nie, S., Guo, H. A., Lu, C., Zhou, Y., Zheng, C., and Li, C · 2023
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OpenAI · 2023
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Sdxl: improving latent diffusion models for high-resolution image synthesis
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Score-based continuous-time discrete diffusion models, 2023
Sun, H., Yu, L., Dai, B., Schuurmans, D., and Dai, H · 2023
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Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation
Wang, Z., Lu, C., Wang, Y., Bao, F., Li, C., Su, H., and Zhu, J · 2023
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Dinoiser: Diffused conditional sequence learning by manipulating noises, 2023
Ye, J., Zheng, Z., Bao, Y., Qian, L., and Wang, M · 2023
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Unipc: A unified predictor-corrector framework for fast sampling of diffusion models
Zhao, W., Bai, L., Rao, Y., Zhou, J., and Lu, J · 2023
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