russellkim / diffusion_models

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Survey

Luo, Calvin. 2022. “Understanding Diffusion Models: A Unified Perspective.” arXiv [cs.LG]. arXiv. http://arxiv.org/abs/2208.11970.

Yang, Ling, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Wentao Zhang, Bin Cui, and Ming-Hsuan Yang. 2022. “Diffusion Models: A Comprehensive Survey of Methods and Applications.” arXiv [cs.LG]. arXiv. http://arxiv.org/abs/2209.00796v10.

Cao, Hanqun, Cheng Tan, Zhangyang Gao, Yilun Xu, Guangyong Chen, Pheng-Ann Heng, and Stan Z. Li. 2022. “A Survey on Generative Diffusion Model.” arXiv [cs.AI]. arXiv. http://arxiv.org/abs/2209.02646.

RecSys

Li, Zihao, Aixin Sun, and Chenliang Li. 2023. “DiffuRec: A Diffusion Model for Sequential Recommendation.” arXiv [cs.IR]. arXiv. http://arxiv.org/abs/2304.00686.

Liu, Qidong, Fan Yan, Xiangyu Zhao, Zhaocheng Du, Huifeng Guo, Ruiming Tang, and Feng Tian. 2023. “Diffusion Augmentation for Sequential Recommendation.” In. http://arxiv.org/abs/2309.12858.

Yu, Penghang, Zhiyi Tan, Guanming Lu, and Bing-Kun Bao. 2023. “LD4MRec: Simplifying and Powering Diffusion Model for Multimedia Recommendation.” arXiv [cs.IR]. arXiv. http://arxiv.org/abs/2309.15363.

Zhang, Lingzi, Yong Liu, Xin Zhou, Chunyan Miao, Guoxin Wang, and Haihong Tang. 2022. “Diffusion-Based Graph Contrastive Learning for Recommendation with Implicit Feedback.” In Database Systems for Advanced Applications, 232–47. Springer International Publishing.

Du, Boxin, Lihui Liu, Jiejun Xu, Fei Wang, and Hanghang Tong. 2023. “Neural Multi-Network Diffusion towards Social Recommendation.” arXiv [cs.LG]. arXiv. http://arxiv.org/abs/2304.04994.

Etc

Azizi, Shekoofeh, Simon Kornblith, Chitwan Saharia, Mohammad Norouzi, and David J. Fleet. 2023. “Synthetic Data from Diffusion Models Improves ImageNet Classification.” arXiv [cs.CV]. arXiv. http://arxiv.org/abs/2304.08466.

Gasteiger, Johannes, Stefan Weißenberger, and Stephan Günnemann. 2019. “Diffusion Improves Graph Learning.” In. https://proceedings.neurips.cc/paper/2019/hash/23c894276a2c5a16470e6a31f4618d73-Abstract.html.

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