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Score-based distillation methods (e.g., variational score distillation) train one-step diffusion models by first pre-training a teacher score model and then distilling it into a one-step student model.
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Estimation of non-normalized statistical models by score matching
Hyvärinen, A · 2005
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Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L · 2009
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Learning multiple layers of features from tiny images
Krizhevsky, A · 2009
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Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
Gutmann, M. and Hyvärinen, A · 2010
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Tweedie’s formula and selection bias
Efron, B · 2011
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A connection between score matching and denoising autoencoders
Vincent, P · 2011
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Density ratio estimation in machine learning
Sugiyama, M., Suzuki, T., and Kanamori, T · 2012
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Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
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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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f-gan: Training generative neural samplers using variational divergence minimization
Nowozin, S., Cseke, B., and Tomioka, R · 2016
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Amortised map inference for image super-resolution
Sønderby, C. K., Caballero, J., Theis, L., Shi, W., and Huszár, F · 2016
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Towards principled methods for training generative adversarial networks
Arjovsky, M. and Bottou, L · 2017
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Wasserstein generative adversarial networks
Arjovsky, M., Chintala, S., and Bottou, L · 2017
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Many paths to equilibrium: Gans do not need to decrease a divergence at every step
Fedus, W., Rosca, M., Lakshminarayanan, B., Dai, A. M., Mohamed, S., and Goodfellow, I · 2017
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Improved training of wasserstein gans
Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., and Courville, A. C · 2017
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Variational inference using implicit distributions
Huszár, F · 2017
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Stabilizing training of generative adversarial networks through regularization
Roth, K., Lucchi, A., Nowozin, S., and Hofmann, T · 2017
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Which training methods for gans do actually converge?
Mescheder, L., Geiger, A., and Nowozin, S · 2018
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Spectral normalization for generative adversarial networks
Miyato, T., Kataoka, T., Koyama, M., and Yoshida, Y · 2018
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Generative modeling by estimating gradients of the data distribution
Song, Y. and Ermon, S · 2019
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Variational f-divergence minimization
Zhang, M., Bird, T., Habib, R., Xu, T., and Barber, D · 2019
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Generalized energy based models
Arbel, M., Zhou, L., and Gretton, A · 2020
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Your gan is secretly an energy-based model and you should use discriminator driven latent sampling
Che, T., Zhang, R., Sohl-Dickstein, J., Larochelle, H., Paull, L., Cao, Y., and Bengio, Y · 2020
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Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
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Diffusion-GAN: Training GANs with diffusion
Wang, Z., Zheng, H., He, P., Chen, W., and Zhou, M · 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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One step diffusion via shortcut models
Frans, K., Hafner, D., Levine, S., and Abbeel, P · 2024
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Training neural samplers with reverse diffusive kl divergence
He, J., Chen, W., Zhang, M., Barber, D., and Hernández-Lobato, J. M · 2024
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Heek, J., Hoogeboom, E., and Salimans, T · 2024
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Song, J., Meng, C., and Ermon, S · 2020
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Spread divergence
Zhang, M., Hayes, P., Bird, T., Habib, R., and Barber, D · 2020
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Adversarial score identity distillation: Rapidly surpassing the teacher in one step
Zhou, M., Zheng, H., Gu, Y., Wang, Z., and Huang, H · 2020
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Improved denoising diffusion probabilistic models
Nichol, A. Q. and Dhariwal, P · 2021
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Tackling the generative learning trilemma with denoising diffusion gans
Xiao, Z., Kreis, K., and Vahdat, A · 2021
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Video diffusion models
Ho, J., Salimans, T., Gritsenko, 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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Analyzing and improving the training dynamics of diffusion models
Karras, T., Aittala, M., Lehtinen, J., Hellsten, J., Aila, T., and Laine, S · 2024
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Consistency trajectory models: Learning probability flow ODE trajectory of diffusion
Kim, D., Lai, C.-H., Liao, W.-H., Murata, N., Takida, Y., Uesaka, T., He, Y., Mitsufuji, Y., and Ermon, S · 2024
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Bidirectional consistency models
Li, L. and He, J · 2024
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Diff-instruct: A universal approach for transferring knowledge from pre-trained diffusion models
Luo, W., Hu, T., Zhang, S., Sun, J., Li, Z., and Zhang, Z · 2024
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Multistep distillation of diffusion models via moment matching
Salimans, T., Mensink, T., Heek, J., and Hoogeboom, E · 2024
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Improved techniques for training consistency models
Song, Y. and Dhariwal, P · 2024
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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 · 2024
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Em distillation for one-step diffusion models
Xie, S., Xiao, Z., Kingma, D. P., Hou, T., Wu, Y. N., Murphy, K. P., Salimans, T., Poole, B., and Gao, R · 2024
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Improved distribution matching distillation for fast image synthesis
Yin, T., Gharbi, M., Park, T., Zhang, R., Shechtman, E., Durand, F., and Freeman, B · 2024
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Hierarchical semi-implicit variational inference with application to diffusion model acceleration
Yu, L., Xie, T., Zhu, Y., Yang, T., Zhang, X., and Zhang, C · 2024
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Score identity distillation: Exponentially fast distillation of pretrained diffusion models for one-step generation
Zhou, M., Zheng, H., Wang, Z., Yin, M., and Huang, H · 2024
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Flow map matching with stochastic interpolants: A mathematical framework for consistency models
Boffi, N. M., Albergo, M. S., and Vanden-Eijnden, E · 2025
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Distributional diffusion models with scoring rules, 2025
Bortoli, V. D., Galashov, A., Guntupalli, J. S., Zhou, G., Murphy, K., Gretton, A., and Doucet, A · 2025
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Simplifying, stabilizing and scaling continuous-time consistency models
Lu, C. and Song, Y · 2025
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Improving probabilistic diffusion models with optimal covariance matching
Ou, Z., Zhang, M., Zhang, A., Xiao, T. Z., Li, Y., and Barber, D · 2025
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Vardiu: A variational diffusive upper bound for one-step diffusion distillation
Wang, L., Zhang, M., Ou, Z., and Barber, D · 2025
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