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This paper investigates energy guidance in generative modeling, where the target distribution is defined as $q(\mathbf x) \propto p(\mathbf x)\exp(-\beta \mathcal E(\mathbf x))$, with $p(\mathbf x)$ being the data distribution and $\mathcal E(\mathcal x)$ as the energy function.
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E (n) equivariant graph neural networks
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Equivariant diffusion for molecule generation in 3d
Emiel Hoogeboom, Vıctor Garcia Satorras, Clément Vignac, and Max Welling · 2022
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Diffcps: Diffusion model based constrained policy search for offline reinforcement learning
Longxiang He, Linrui Zhang, Junbo Tan, and Xueqian Wang · 2023
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Contrastive energy prediction for exact energy-guided diffusion sampling in offline reinforcement learning
Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, and Jun Zhu · 2023
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Sdxl: Improving latent diffusion models for high-resolution image synthesis
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2023
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Julian Cremer, Tuan Le, Frank Noé, Djork-Arné Clevert, and Kristof T Schütt · 2024
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Diffusion-based reinforcement learning via q-weighted variational policy optimization
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Michael Janner, Yilun Du, Joshua Tenenbaum, and Sergey Levine · 2022
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Yaron Lipman, Ricky TQ Chen, Heli Ben-Hamu, Maximilian Nickel, and Matthew Le · 2022
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Rectified flow: A marginal preserving approach to optimal transport
Qiang Liu · 2022
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Diffusion policies as an expressive policy class for offline reinforcement learning
Zhendong Wang, Jonathan J Hunt, and Mingyuan Zhou · 2022
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Score regularized policy optimization through diffusion behavior
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Philippe Hansen-Estruch, Ilya Kostrikov, Michael Janner, Jakub Grudzien Kuba, and Sergey Levine · 2023
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Shutong Ding, Ke Hu, Zhenhao Zhang, Kan Ren, Weinan Zhang, Jingyi Yu, Jingya Wang, and Ye Shi · 2024
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Zeyu Fang and Tian Lan · 2024
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Matthew Thomas Jackson, Michael Tryfan Matthews, Cong Lu, Benjamin Ellis, Shimon Whiteson, and Jakob Foerster · 2024
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Efficient diffusion policies for offline reinforcement learning
Bingyi Kang, Xiao Ma, Chao Du, Tianyu Pang, and Shuicheng Yan · 2024
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Gta: Generative trajectory augmentation with guidance for offline reinforcement learning
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Synthetic experience replay
Cong Lu, Philip Ball, Yee Whye Teh, and Jack Parker-Holder · 2024
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Improved off-policy training of diffusion samplers
Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, and Nikolay Malkin · 2024
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Protein conformation generation via force-guided se (3) diffusion models
Yan Wang, Lihao Wang, Yuning Shen, Yiqun Wang, Huizhuo Yuan, Yue Wu, and Quanquan Gu · 2024
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