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Found 5 papers, 2 papers with code
Continuous-time Autoencoders for Regular and Irregular Time Series Imputation
However, it has been overlooked for a long time to design an imputation method based on continuous-time recurrent neural networks (RNNs), i. e., neural controlled differential equations (NCDEs).
An Attentive Inductive Bias for Sequential Recommendation beyond the Self-Attention
In the SR domain, we, for the first time, show that the same problem occurs.
Ranked #1 on
Sequential Recommendation
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Polynomial-based Self-Attention for Table Representation learning
Structured data, which constitutes a significant portion of existing data types, has been a long-standing research topic in the field of machine learning.
Graph Convolutions Enrich the Self-Attention in Transformers!
We propose a graph-filter-based self-attention (GFSA) to learn a general yet effective one, whose complexity, however, is slightly larger than that of the original self-attention mechanism.
SOS: Score-based Oversampling for Tabular Data
To our knowledge, we are the first presenting a score-based tabular data oversampling method.
