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Found 4 papers, 1 papers with code
Time-SSM: Simplifying and Unifying State Space Models for Time Series Forecasting
State Space Models (SSMs) have emerged as a potent tool in sequence modeling tasks in recent years.
BiVRec: Bidirectional View-based Multimodal Sequential Recommendation
The integration of multimodal information into sequential recommender systems has attracted significant attention in recent research.
Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective
In long-term time series forecasting (LTSF) tasks, an increasing number of models have acknowledged that discrete time series originate from continuous dynamic systems and have attempted to model their dynamical structures.
Multimodal Recommender Systems: A Survey
In this paper, we will give a comprehensive survey of the MRS models, mainly from technical views.
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