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Diffusion models have recently been increasingly applied to temporal data such as video, fluid mechanics simulations, or climate data.
Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J., Weiss, E. A., Maheswaranathan, N., and Ganguli, S · 2015
Earlier work this paper cites.
Quo vadis, action recognition? a new model and the kinetics dataset
Carreira, J. and Zisserman, A · 2017
Earlier work this paper cites.
Self-supervised visual planning with temporal skip connections
Ebert, F., Finn, C., Lee, A. X., and Levine, S · 2017
Earlier work this paper cites.
The kinetics human action video dataset
Kay, W., Carreira, J., Simonyan, K., Zhang, B., Hillier, C., Vijayanarasimhan, S., Viola, F., Green, T., Back, T., Natsev, P., et al · 2017
Earlier work this paper cites.
A short note about kinetics-600
Carreira, J., Noland, E., Banki-Horvath, A., Hillier, C., and Zisserman, A · 2018
Earlier work this paper cites.
Adversarial video generation on complex datasets
Clark, A., Donahue, J., and Simonyan, K · 2019
Earlier work this paper cites.
Generative modeling by estimating gradients of the data distribution
Song, Y. and Ermon, S · 2019
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Fvd: A new metric for video generation
Unterthiner, T., van Steenkiste, S., Kurach, K., Marinier, R., Michalski, M., and Gelly, S · 2019
Earlier work this paper cites.
Scaling autoregressive video models
Weissenborn, D., Täckström, O., and Uszkoreit, J · 2019
Earlier work this paper cites.
Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
Earlier work this paper cites.
Fourier neural operator for parametric partial differential equations
Li, Z., Kovachki, N., Azizzadenesheli, K., Liu, B., Bhattacharya, K., Stuart, A., and Anandkumar, A · 2020
Earlier work this paper cites.
Transformation-based adversarial video prediction on large-scale data
Luc, P., Clark, A., Dieleman, S., Casas, D. d. L., Doron, Y., Cassirer, A., and Simonyan, K · 2020
Earlier work this paper cites.
Fitvid: Overfitting in pixel-level video prediction
Babaeizadeh, M., Saffar, M. T., Nair, S., Levine, S., Finn, C., and Erhan, D · 2021
Earlier work this paper cites.
Kingma, D. P., Salimans, T., Poole, B., and Ho, J · 2021
Earlier work this paper cites.
Machine learning–accelerated computational fluid dynamics
Kochkov, D., Smith, J. A., Alieva, A., Wang, Q., Brenner, M. P., and Hoyer, S · 2021
Earlier work this paper cites.
DiffWave: A versatile diffusion model for audio synthesis
Kong, Z., Ping, W., Huang, J., Zhao, K., and Catanzaro, B · 2021
Earlier work this paper cites.
Ccvs: context-aware controllable video synthesis
Le Moing, G., Ponce, J., and Schmid, C · 2021
Earlier work this paper cites.
Csdi: Conditional score-based diffusion models for probabilistic time series imputation
Tashiro, Y., Song, J., Song, Y., and Ermon, S · 2021
Cited alongside, same era.
Videogpt: Video generation using vq-vae and transformers
Yan, W., Zhang, Y., Abbeel, P., and Srinivas, A · 2021
Cited alongside, same era.
Learning to correct spectral methods for simulating turbulent flows
Dresdner, G., Kochkov, D., Norgaard, P., Zepeda-Núñez, L., Smith, J. A., Brenner, M. P., and Hoyer, S · 2022
Cited alongside, same era.
Flexible diffusion modeling of long videos
Harvey, W., Naderiparizi, S., Masrani, V., Weilbach, C., and Wood, F · 2022
Cited alongside, same era.
Latent video diffusion models for high-fidelity video generation with arbitrary lengths
He, Y., Yang, T., Zhang, Y., Shan, Y., and Chen, Q · 2022
Dyffusion: A dynamics-informed diffusion model for spatiotemporal forecasting
Cachay, S. R., Zhao, B., James, H., and Yu, R · 2023
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E3 tts: Easy end-to-end diffusion-based text to speech
Gao, Y., Morioka, N., Zhang, Y., and Chen, N · 2023
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Preserve your own correlation: A noise prior for video diffusion models
Ge, S., Nah, S., Liu, G., Poon, T., Tao, A., Catanzaro, B., Jacobs, D., Huang, J.-B., Liu, M.-Y., and Balaji, Y · 2023
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Photorealistic video generation with diffusion models
Gupta, A., Yu, L., Sohn, K., Gu, X., Hahn, M., Fei-Fei, L., Essa, I., Jiang, L., and Lezama, J · 2023
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simple diffusion: End-to-end diffusion for high resolution images
Hoogeboom, E., Heek, J., and Salimans, T · 2023
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Cited alongside, same era.
Scalable adaptive computation for iterative generation
Jabri, A., Fleet, D. J., and Chen, T · 2022
Cited alongside, same era.
Diffusion-lm improves controllable text generation
Li, X., Thickstun, J., Gulrajani, I., Liang, P. S., and Hashimoto, T. B · 2022
Cited alongside, same era.
On distillation of guided diffusion models
Meng, C., Gao, R., Kingma, D. P., Ermon, S., Ho, J., and Salimans, T · 2022
Cited alongside, same era.
Transframer: Arbitrary frame prediction with generative models
Nash, C., Carreira, J., Walker, J., Barr, I., Jaegle, A., Malinowski, M., and Battaglia, P · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with CLIP latents
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., and Chen, M · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B · 2022
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding
Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E., Ghasemipour, S. K. S., Ayan, B. K., Mahdavi, S. S., Lopes, R. G., Salimans, T., Ho, J., Fleet, D. J., and Norouzi, M · 2022
Cited alongside, same era.
Later among the works it cites.
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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Understanding diffusion objectives as the elbo with simple data augmentation
Kingma, D. P. and Gao, R · 2023
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Turbulent flow simulation using autoregressive conditional diffusion models
Kohl, G., Chen, L.-W., and Thuerey, N · 2023
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Pde-refiner: Achieving accurate long rollouts with neural pde solvers
Lippe, P., Veeling, B. S., Perdikaris, P., Turner, R. E., and Brandstetter, J · 2023
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Gencast: Diffusion-based ensemble forecasting for medium-range weather
Price, I., Sanchez-Gonzalez, A., Alet, F., Ewalds, T., El-Kadi, A., Stott, J., Mohamed, S., Battaglia, P., Lam, R., and Willson, M · 2023
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A neural pde solver with temporal stencil modeling
Sun, Z., Yang, Y., and Yoo, S · 2023
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Ar-diffusion: Auto-regressive diffusion model for text generation
Wu, T., Fan, Z., Liu, X., Gong, Y., Shen, Y., Jiao, J., Zheng, H.-T., Li, J., Wei, Z., Guo, J., et al · 2023
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Temporally consistent transformers for video generation
Yan, W., Hafner, D., James, S., and Abbeel, P · 2023
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Diffusion probabilistic modeling for video generation
Yang, R., Srivastava, P., and Mandt, S · 2023
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Tedi: Temporally-entangled diffusion for long-term motion synthesis
Zhang, Z., Liu, R., Aberman, K., and Hanocka, R · 2023
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Introducing stable video diffusion
StabilityAI · 2024
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