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Diffusion-based generative models use stochastic differential equations (SDEs) and their equivalent ordinary differential equations (ODEs) to establish a smooth connection between a complex data distribution and a tractable prior distribution.
Differentiable manifolds
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Comaniciu, D., Ramesh, V., and Meer, P · 2000
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Mean shift: A robust approach toward feature space analysis
Comaniciu, D. and Meer, P · 2002
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Kernel-based object tracking
Comaniciu, D., Ramesh, V., and Meer, P · 2003
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Estimation of non-normalized statistical models by score matching
Hyvärinen, A · 2005
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Fast global kernel density mode seeking with application to localisation and tracking
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Krizhevsky, A. and Hinton, G · 2009
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Interpretation and generalization of score matching
Lyu, S · 2009
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Raphan, M. and Simoncelli, E. P · 2011
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A connection between score matching and denoising autoencoders
Vincent, P · 2011
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Generalized denoising auto-encoders as generative models
Bengio, Y., Yao, L., Alain, G., and Vincent, P · 2013
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Oksendal, B · 2013
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Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., and Zitnick, C. L · 2014
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A review of mean-shift algorithms for clustering
Carreira-Perpinán, M. A · 2015
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Imagenet large scale visual recognition challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M. S., Berg, A. C., and Li, F · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
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Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
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GANs trained by a two time-scale update rule converge to a local Nash equilibrium
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High-dimensional probability: An introduction with applications in data science , volume 47
Vershynin, R · 2018
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Video diffusion models
Ho, J., Salimans, T., Gritsenko, A. A., Chan, W., Norouzi, M., and Fleet, D. J · 2022
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Elucidating the design space of diffusion-based generative models
Karras, T., Aittala, M., Aila, T., and Laine, S · 2022
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Pseudo numerical methods for diffusion models on manifolds
Liu, L., Ren, Y., Lin, Z., and Zhao, Z · 2022
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Score-based generative models detect manifolds
Pidstrigach, J · 2022
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Hierarchical text-conditional image generation with clip latents
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., and Chen, M · 2022
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High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B · 2022
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A style-based generator architecture for generative adversarial networks
Karras, T., Laine, S., and Aila, T · 2019
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Applied stochastic differential equations , volume 10
Särkkä, S. and Solin, A · 2019
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Generative modeling by estimating gradients of the data distribution
Song, Y. and Ermon, S · 2019
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Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
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Improved techniques for training score-based generative models
Song, Y. and Ermon, S · 2020
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Properties of mean shift
Yamasaki, R. and Tanaka, T · 2020
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Diffusion models beat gans on image synthesis
Dhariwal, P. and Nichol, A · 2021
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Photorealistic text-to-image diffusion models with deep language understanding
Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E. L., Ghasemipour, K., Gontijo Lopes, R., Karagol Ayan, B., Salimans, T., et al · 2022
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Progressive distillation for fast sampling of diffusion models
Salimans, T. and Ho, J · 2022
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Align your latents: High-resolution video synthesis with latent diffusion models
Blattmann, A., Rombach, R., Ling, H., Dockhorn, T., Kim, S. W., Fidler, S., and Kreis, K · 2023
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Diffusion models already have a semantic latent space
Kwon, M., Jeong, J., and Uh, Y · 2023
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Convergence of score-based generative modeling for general data distributions
Lee, H., Lu, J., and Tan, Y · 2023
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Ruiz, N., Li, Y., Jampani, V., Pritch, Y., Rubinstein, M., and Aberman, K · 2023
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Consistency models
Song, Y., Dhariwal, P., Chen, M., and Sutskever, I · 2023
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Stable target field for reduced variance score estimation in diffusion models
Xu, Y., Tong, S., and Jaakkola, T. S · 2023
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Physdiff: Physics-guided human motion diffusion model
Yuan, Y., Song, J., Iqbal, U., Vahdat, A., and Kautz, J · 2023
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Fast sampling of diffusion models with exponential integrator
Zhang, Q. and Chen, Y · 2023
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Improved order analysis and design of exponential integrator for diffusion models sampling
Zhang, Q., Song, J., and Chen, Y · 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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Fast sampling of diffusion models via operator learning
Zheng, H., Nie, W., Vahdat, A., Azizzadenesheli, K., and Anandkumar, A · 2023
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Fast ode-based sampling for diffusion models in around 5 steps
Zhou, Z., Chen, D., Wang, C., and Chen, C · 2023
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Scaling rectified flow transformers for high-resolution image synthesis
Esser, P., Kulal, S., Blattmann, A., Entezari, R., Müller, J., Saini, H., Levi, Y., Lorenz, D., Sauer, A., Boesel, F., et al · 2024
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Sdxl: Improving latent diffusion models for high-resolution image synthesis
Podell, D., English, Z., Lacey, K., Blattmann, A., Dockhorn, T., Müller, J., Penna, J., and Rombach, R · 2024
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Align your steps: Optimizing sampling schedules in diffusion models
Sabour, A., Fidler, S., and Kreis, K · 2024
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