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Diffusion policies excel at learning complex action distributions for robotic visuomotor tasks, yet their iterative denoising process poses a major bottleneck for real-time deployment.
Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning
Gupta, A.; Kumar, V.; Lynch, C.; Levine, S.; and Hausman, K. 2019 · 1910
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Denoising diffusion implicit models
Song, J.; Meng, C.; and Ermon, S. 2020 · 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. 2020 · 2011
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Auto-encoding variational bayes
Kingma, D. P.; Welling, M.; et al. 2013 · 2013
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High-dimensional continuous control using generalized advantage estimation
Schulman, J.; Moritz, P.; Levine, S.; Jordan, M.; and Abbeel, P. 2015 · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J.; Weiss, E.; Maheswaranathan, N.; and Ganguli, S. 2015 · 2015
Earlier work this paper cites.
Sgdr: Stochastic gradient descent with warm restarts
Loshchilov, I.; and Hutter, F. 2016 · 2016
Earlier work this paper cites.
Proximal policy optimization algorithms
Schulman, J.; Wolski, F.; Dhariwal, P.; Radford, A.; and Klimov, O. 2017 · 2017
Earlier work this paper cites.
Generative adversarial networks
Goodfellow, I.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A.; and Bengio, Y. 2020 · 2020
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Denoising diffusion probabilistic models
Ho, J.; Jain, A.; and Abbeel, P. 2020 · 2020
Earlier work this paper cites.
What Matters in Learning from Offline Human Demonstrations for Robot Manipulation
Mandlekar, A.; Xu, D.; Wong, J.; Nasiriany, S.; Wang, C.; Kulkarni, R.; Fei-Fei, L.; Savarese, S.; Zhu, Y.; and Martín-Martín, R. 2021 · 2021
Cited alongside, same era.
High-Resolution Image Synthesis with Latent Diffusion Models
Rombach, R.; Blattmann, A.; Lorenz, D.; Esser, P.; and Ommer, B. 2021 · 2021
Cited alongside, same era.
Planning with Diffusion for Flexible Behavior Synthesis
Janner, M.; Du, Y.; Tenenbaum, J.; and Levine, S. 2022 · 2022
Cited alongside, same era.
Behavior transformers: Cloning k k modes with one stone
Shafiullah, N. M.; Cui, Z.; Altanzaya, A. A.; and Pinto, L. 2022 · 2022
Cited alongside, same era.
Diffusion policies as an expressive policy class for offline reinforcement learning
Wang, Z.; Hunt, J. J.; and Zhou, M. 2022 · 2022
Policy representation via diffusion probability model for reinforcement learning
Yang, L.; Huang, Z.; Lei, F.; Zhong, Y.; Yang, Y.; Fang, C.; Wen, S.; Zhou, B.; and Lin, Z. 2023 · 2023
Later among the works it cites.
Learning fine-grained bimanual manipulation with low-cost hardware
Zhao, T. Z.; Kumar, V.; Levine, S.; and Finn, C. 2023 · 2023
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Streaming Diffusion Policy: Fast Policy Synthesis with Variable Noise Diffusion Models
Høeg, S. H.; Du, Y.; and Egeland, O. 2024 · 2024
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Learning multimodal behaviors from scratch with diffusion policy gradient
Li, S.; Krohn, R.; Chen, T.; Ajay, A.; Agrawal, P.; and Chalvatzaki, G. 2024 · 2024
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Hierarchical diffusion policy for kinematics-aware multi-task robotic manipulation
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Cited alongside, same era.
Diffusion policy: Visuomotor policy learning via action diffusion
Chi, C.; Xu, Z.; Feng, S.; Cousineau, E.; Du, Y.; Burchfiel, B.; Tedrake, R.; and Song, S. 2023 · 2023
Cited alongside, same era.
Idql: Implicit q-learning as an actor-critic method with diffusion policies
Hansen-Estruch, P.; Kostrikov, I.; Janner, M.; Kuba, J. G.; and Levine, S. 2023 · 2023
Cited alongside, same era.
Efficient diffusion policies for offline reinforcement learning
Kang, B.; Ma, X.; Du, C.; Pang, T.; and Yan, S. 2023 · 2023
Cited alongside, same era.
Imitating Human Behaviour with Diffusion Models
Pearce, T.; Rashid, T.; Kanervisto, A.; Bignell, D.; Sun, M.; Georgescu, R.; Macua, S. V.; Tan, S. Z.; Momennejad, I.; Hofmann, K.; and Devlin, S. 2023 · 2023
Cited alongside, same era.
Learning a diffusion model policy from rewards via q-score matching
Psenka, M.; Escontrela, A.; Abbeel, P.; and Ma, Y. 2023 · 2023
Cited alongside, same era.
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. 2022a
Cited in the paper.
Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models
Lu, C.; Zhou, Y.; Bao, F.; Chen, J.; Li, C.; and Zhu, J. 2022b
Cited in the paper.
Ma, X.; Patidar, S.; Haughton, I.; and James, S. 2024 · 2024
Later among the works it cites.
Consistency policy: Accelerated visuomotor policies via consistency distillation
Prasad, A.; Lin, K.; Wu, J.; Zhou, L.; and Bohg, J. 2024 · 2024
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Diffusion policy policy optimization
Ren, A. Z.; Lidard, J.; Ankile, L. L.; Simeonov, A.; Agrawal, P.; Majumdar, A.; Burchfiel, B.; Dai, H.; and Simchowitz, M. 2024 · 2024
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3d diffusion policy: Generalizable visuomotor policy learning via simple 3d representations
Ze, Y.; Zhang, G.; Zhang, K.; Hu, C.; Wang, M.; and Xu, H. 2024 · 2024
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Falcon: Fast Visuomotor Policies via Partial Denoising
Chen, H.; Liu, M.; Ma, C.; Ma, X.; Ma, Z.; Wu, H.; Chen, Y.; Zhong, Y.; Wang, M.; Li, Q.; and Yang, Y. 2025 · 2025
Closest in time.
Schedule on the fly: Diffusion time prediction for faster and better image generation
Ye, Z.; Chen, Z.; Li, T.; Huang, Z.; Luo, W.; and Qi, G.-J. 2025 · 2025
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