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Pioneering efforts have verified the effectiveness of the diffusion models in exploring the informative uncertainty for recommendation.
Auto-encoding variational bayes
Kingma, D. P.; and Welling, M. 2013 · 2013
Earlier work this paper cites.
Session-based recommendations with recurrent neural networks
Hidasi, B.; Karatzoglou, A.; Baltrunas, L.; and Tikk, D. 2016 · 2016
Earlier work this paper cites.
Neural attentive session-based recommendation
Li, J.; Ren, P.; Chen, Z.; Ren, Z.; Lian, T.; and Ma, J. 2017 · 2017
Earlier work this paper cites.
Self-attentive sequential recommendation
Kang, W.-C.; and McAuley, J. 2018 · 2018
Earlier work this paper cites.
Personalized top-n sequential recommendation via convolutional sequence embedding
Tang, J.; and Wang, K. 2018 · 2018
Earlier work this paper cites.
BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer
Sun, F.; Liu, J.; Wu, J.; Pei, C.; Lin, X.; Ou, W.; and Jiang, P. 2019 · 2019
Earlier work this paper cites.
Recurrent convolutional neural network for sequential recommendation
Xu, C.; Zhao, P.; Liu, Y.; Xu, J.; S. Sheng, V. S. S.; Cui, Z.; Zhou, X.; and Xiong, H. 2019 · 2019
Earlier work this paper cites.
Denoising diffusion probabilistic models
Ho, J.; Jain, A.; and Abbeel, P. 2020 · 2020
Earlier work this paper cites.
Heterogeneous fusion of semantic and collaborative information for visually-aware food recommendation
Meng, L.; Feng, F.; He, X.; Gao, X.; and Chua, T.-S. 2020 · 2020
Earlier work this paper cites.
Comparative study of adversarial training methods for cold-start recommendation
Ma, H.; Li, X.; Meng, L.; and Meng, X. 2021 · 2021
Earlier work this paper cites.
Improved denoising diffusion probabilistic models
Nichol, A. Q.; and Dhariwal, P. 2021 · 2021
Cited alongside, same era.
Csdi: Conditional score-based diffusion models for probabilistic time series imputation
Tashiro, Y.; Song, J.; Song, Y.; and Ermon, S. 2021 · 2021
Cited alongside, same era.
Knowledge-enhanced hierarchical graph transformer network for multi-behavior recommendation
Xia, L.; Huang, C.; Xu, Y.; Dai, P.; Zhang, X.; Yang, H.; Pei, J.; and Bo, L. 2021 · 2021
Cited alongside, same era.
Denoising pretraining for semantic segmentation
Brempong, E. A.; Kornblith, S.; Chen, T.; Parmar, N.; Minderer, M.; and Norouzi, M. 2022 · 2022
Cited alongside, same era.
Intent contrastive learning for sequential recommendation
Chen, Y.; Liu, Z.; Li, J.; McAuley, J.; and Xiong, C. 2022 · 2022
Cited alongside, same era.
Cascaded diffusion models for high fidelity image generation
Contrastive learning for sequential recommendation
Xie, X.; Sun, F.; Liu, Z.; Wu, S.; Gao, J.; Zhang, J.; Ding, B.; and Cui, B. 2022 · 2022
Later among the works it cites.
Dynamic graph neural networks for sequential recommendation
Zhang, M.; Wu, S.; Yu, X.; Liu, Q.; and Wang, L. 2022 · 2022
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DDGHM: Dual Dynamic Graph with Hybrid Metric Training for Cross-Domain Sequential Recommendation
Zheng, X.; Su, J.; Liu, W.; and Chen, C. 2022 · 2022
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Sequential Recommendation with Diffusion Models
Du, H.; Yuan, H.; Huang, Z.; Zhao, P.; and Zhou, X. 2023 · 2023
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DiffuRec: A Diffusion Model for Sequential Recommendation
Li, Z.; Sun, A.; and Li, C. 2023 · 2023
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Ho, J.; Saharia, C.; Chan, W.; Fleet, D. J.; Norouzi, M.; and Salimans, T. 2022 · 2022
Cited alongside, same era.
MLP4Rec: A Pure MLP Architecture for Sequential Recommendations
Li, M.; Zhao, X.; Lyu, C.; Zhao, M.; Wu, R.; and Guo, R. 2022 · 2022
Cited alongside, same era.
Dual Contrastive Network for Sequential Recommendation with User and Item-Centric Perspectives
Lin, G.; Gao, C.; Li, Y.; Zheng, Y.; Li, Z.; Jin, D.; and Li, Y. 2022 · 2022
Cited alongside, same era.
Conditional simulation using diffusion Schrödinger bridges
Shi, Y.; De Bortoli, V.; Deligiannidis, G.; and Doucet, A. 2022 · 2022
Cited alongside, same era.
Recommendation via collaborative diffusion generative model
Walker, J.; Zhong, T.; Zhang, F.; Gao, Q.; and Zhou, F. 2022 · 2022
Cited alongside, same era.
Win-Win: A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation
Chen, G.; Zhang, X.; Su, Y.; Lai, Y.; Xiang, J.; Zhang, J.; and Zheng, Y. 2023a
Cited in the paper.
Enhanced Multi-Relationships Integration Graph Convolutional Network for Inferring Substitutable and Complementary Items
Chen, H.; He, J.; Xu, W.; Feng, T.; Liu, M.; Song, T.; Yao, R.; and Qiao, Y. 2023b
Cited in the paper.
Lopez Alcaraz, J. M.; and Strodthoff, N. 2023 · 2023
Later among the works it cites.
CoMix: Collaborative filtering with mixup for implicit datasets
Moon, J.; Jeong, Y.; Chae, D.-K.; Choi, J.; Shim, H.; and Lee, J. 2023 · 2023
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On the Theories Behind Hard Negative Sampling for Recommendation
Shi, W.; Chen, J.; Feng, F.; Zhang, J.; Wu, J.; Gao, C.; and He, X. 2023 · 2023
Later among the works it cites.
Diffusion Recommender Model
Wang, W.; Xu, Y.; Feng, F.; Lin, X.; He, X.; and Chua, T.-S. 2023 · 2023
Later among the works it cites.
Graph-augmented co-attention model for socio-sequential recommendation
Wu, B.; He, X.; Wu, L.; Zhang, X.; and Ye, Y. 2023 · 2023
Later among the works it cites.