[1] Y. Song and S. Ermon, “Generative modeling by estimating gradients of the data distribution”, NeurIPS, 2019.
[2] P. Dhariwal and A. Nichol, “DIfffusion models beat GANs on image synthesis”, NeurIPS, 2021.
[3] A. Nichol, P. Dhariwal, A. Ramesh, P. Shyam, P. Mishkin, B. McGrew, I. Sutskever, and M. Chen, “GLIDE: Towards photorealistic image generation and editing with text-guided diffusion models”, ICML, 2021.
[4] T. Karras, M. Aittala, T. Aila, and S. Laine, “Elucidating the design space of diffusion-based generative models”, NeurIPS, 2022.
[5] C. Liu, Y. Zhou, F. Bao, J. Chen, C. Li, and J. Zhu, “DPM-Solver: A fast ODE solver for diffusion probabilistic model sampling in around 10 steps”, NeurIPS, 2022.
[6] T. Dockhorn, A. Vahdat, and K. Kreis, “GENIE: High-order denoising diffusion solvers”, NeurIPS, 2022.
[7] D. Kim, B. Na, S. Kwon, D. Lee, W. Kang, and I-C. Moon, “Maximum likelihood training of implicit nonlinear diffusion models”, NeurIPS, 2022.
[8] S. W. Park, H. Kim, K. Lee, and J. Kwon, “Riemannian neural SDE: Learning stochastic representations on manifolds”, NeurIPS, 2022.
[9] B. Kawar, M. Elad, S. Ermon, and J. Song, “Denoising diffusion restoration models”, NeurIPS, 2022.
[10] H. Chung, B. Sim, D. Ryu and J. C. Ye, “Improving diffusion models for inverse problems using manifold constraints”, NeurIPS, 2022.
[11] Hoffmann, Jordan, et al. "Training Compute-Optimal Large Language Models." NeurIPS, 2022.
[12] Alayrac, Jean-Baptiste, et al. "Flamingo: a visual language model for few-shot learning." NeurIPS, 2022.
[13] Shafiullah, Nur Muhammad Mahi, et al. "Behavior Transformers: Cloning k modes with one stone." NeurIPS, 2022.
[14] Chen, Lili, et al. "Decision transformer: Reinforcement learning via sequence modeling." NeurIPS, 2021.
[15] Janner, Michael, Qiyang Li, and Sergey Levine. "Offline reinforcement learning as one big sequence modeling problem." NeurIPS, 2021.
[16] Zheng, Qinqing, Amy Zhang, and Aditya Grover. "Online decision transformer." ICML, 2022.
[17] Xu, Mengdi, et al. "Prompting decision transformer for few-shot policy generalization." ICML, 2022.
[18] Yang, Yaodong, et al. "Transformer-based Working Memory for Multiagent Reinforcement Learning with Action Parsing." NeurIPS, 2022.
[19] Takagi, Shiro. "On the Effect of Pre-training for Transformer in Different Modality on Offline Reinforcement Learning." NeurIPS, 2022.
[20] Wang, Kerong, et al. "Bootstrapped transformer for offline reinforcement learning." NeurIPS, 2022.
[21] Brown, Tom, et al. "Language models are few-shot learners." NeurIPS, 2020.
[22] Dosovitskiy, Alexey, et al. "CARLA: An open urban driving simulator." CoRL, 2017.
[23] Florence, Pete, et al. "Implicit behavioral cloning." CoRL, 2022.
[24] Gupta, Abhishek, et al. "Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning." CoRL, 2019.
