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Sequential recommendation aims to recommend the next item that matches a user's interest, based on the sequence of items he/she interacted with before.
Visualizing data using t-sne
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Generative adversarial nets
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Auto-encoding variational bayes
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Deep neural networks for youtube recommendations
Paul Covington, Jay Adams, and Emre Sargin · 2016
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Session-based recommendations with recurrent neural networks
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Wasserstein generative adversarial networks
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Deep interest network for click-through rate prediction
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Self-attentive sequential recommendation
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Personalized top-n sequential recommendation via convolutional sequence embedding
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Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer
Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou, and Peng Jiang · 2019
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A simple convolutional generative network for next item recommendation
Fajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose, and Xiangnan He · 2019
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Generative modeling by estimating gradients of the data distribution
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BIVA: A very deep hierarchy of latent variables for generative modeling
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Improved techniques for training score-based generative models
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Score-based generative modeling through stochastic differential equations
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Lighter and better: Low-rank decomposed self-attention networks for next-item recommendation
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Diffusion models beat gans on image synthesis
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High-resolution image synthesis with latent diffusion models
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
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Diffusion models: A comprehensive survey of methods and applications
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Classifier-free diffusion guidance
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On the effectiveness of sampled softmax loss for item recommendation
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Kuairec: A fully-observed dataset and insights for evaluating recommender systems
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A generic learning framework for sequential recommendation with distribution shifts
Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen, and Xiang Wang · 2023
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Invariant collaborative filtering to popularity distribution shift
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Sequential recommendation with diffusion models
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