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Diffusion probabilistic models (DPMs) are a new class of generative models that have achieved state-of-the-art generation quality in various domains.
Estimates of the regression coefficient based on kendall’s tau
Sen, P. K · 1968
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Denoising diffusion implicit models
Song, J., Meng, C., and Ermon, S · 2010
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Score-based generative modeling through stochastic differential equations
Song, Y., Sohl-Dickstein, J., Kingma, D. P., Kumar, A., Ermon, S., and Poole, B · 2011
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Auto-encoding variational bayes
Kingma, D. P. and Welling, M · 2013
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Microsoft coco: Common objects in context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., and Zitnick, C. L · 2014
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U-net: Convolutional networks for biomedical image segmentation
Ronneberger, O., Fischer, P., and Brox, T · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., and Ganguli, S · 2015
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Neural architecture search with reinforcement learning
Zoph, B. and Le, Q. V · 2016
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Population based training of neural networks
Jaderberg, M., Dalibard, V., Osindero, S., Czarnecki, W. M., Donahue, J., Razavi, A., Vinyals, O., Green, T., Dunning, I., Simonyan, K., et al · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
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Neural architecture optimization
Luo, R., Tian, F., Qin, T., Chen, E., and Liu, T.-Y · 2018
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Neural architecture search: A survey
Elsken, T., Metzen, J. H., and Hutter, F · 2019
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Regularized evolution for image classifier architecture search
Real, E., Aggarwal, A., Huang, Y., and Le, Q. V · 2019
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Generative modeling by estimating gradients of the data distribution
Song, Y. and Ermon, S · 2019
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Oboe: Collaborative filtering for automl model selection
Yang, C., Akimoto, Y., Kim, D. W., and Udell, M · 2019
Cited alongside, same era.
Wavegrad: Estimating gradients for waveform generation
Chen, N., Zhang, Y., Zen, H., Weiss, R. J., Norouzi, M., and Chan, W · 2020
Cited alongside, same era.
Generative adversarial networks
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
Cited alongside, same era.
Diffwave: A versatile diffusion model for audio synthesis
Kong, Z., Ping, W., Huang, J., Zhao, K., and Catanzaro, B · 2020
Cited alongside, same era.
Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models
Bao, F., Li, C., Zhu, J., and Zhang, B · 2022
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Perception prioritized training of diffusion models
Choi, J., Lee, J., Shin, C., Kim, S., Kim, H., and Yoon, S · 2022
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Ho, J., Salimans, T., Gritsenko, A., Chan, W., Norouzi, M., and Fleet, D. J · 2022
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Subspace diffusion generative models
Jing, B., Corso, G., Berlinghieri, R., and Jaakkola, T · 2022
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Srdiff: Single image super-resolution with diffusion probabilistic models
Li, H., Yang, Y., Chang, M., Chen, S., Feng, H., Xu, Z., Li, Q., and Chen, Y · 2022
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Ning, X., Zheng, Y., Zhao, T., Wang, Y., and Yang, H · 2020
Cited alongside, same era.
Diffusion models beat gans on image synthesis
Dhariwal, P. and Nichol, A · 2021
Cited alongside, same era.
Kim, D., Shin, S., Song, K., Kang, W., and Moon, I.-C · 2021
Cited alongside, same era.
Diffusion probabilistic models for 3d point cloud generation
Luo, S. and Hu, W · 2021
Cited alongside, same era.
Improved denoising diffusion probabilistic models
Nichol, A. Q. and Dhariwal, P · 2021
Cited alongside, same era.
Maximum likelihood training of score-based diffusion models
Song, Y., Durkan, C., Murray, I., and Ermon, S · 2021
Cited alongside, same era.
Learning to efficiently sample from diffusion probabilistic models
Watson, D., Ho, J., Norouzi, M., and Chan, W · 2021
Cited alongside, same era.
Pseudo numerical methods for diffusion models on manifolds
Liu, L., Ren, Y., Lin, Z., and Zhao, Z · 2022
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Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps
Lu, C., Zhou, Y., Bao, F., Chen, J., Li, C., and Zhu, J · 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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Image super-resolution via iterative refinement
Saharia, C., Ho, J., Chan, W., Salimans, T., Fleet, D. J., and Norouzi, M · 2022
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Learning fast samplers for diffusion models by differentiating through sample quality
Watson, D., Chan, W., Ho, J., and Norouzi, M · 2022
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Diffusion probabilistic model made slim
Yang, X., Zhou, D., Feng, J., and Wang, X · 2022
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Fast sampling of diffusion models with exponential integrator
Zhang, Q. and Chen, Y · 2022
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Understanding the diffusion objective as a weighted integral of elbos
Kingma, D. P. and Gao, R · 2023
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