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ChrisW09 authored May 25, 2024
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date: 22 April 2024
bibliography: paper.bib

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# 1. Summary

Mambular is a Python library designed to leverage the capabilities of the recently proposed Mamba architecture [@Gu] for deep learning tasks involving tabular datasets. The effectiveness of the attention mechanism, as demonstrated by models such as TabTransformer [@Ahamed] and FT-Transformer [@Gorishnyi1], is extended to these data types, showcasing the potential for sequence-focused architectures to excel in this domain. Thus, sequence-focused architectures can also achieve state-of-the-art performances for tabular data problems. [@Huang] already demonstrated that the Mamba architecture, similar to the attention mechanism, can effectively be used when dealing with tabular data. Mambular closely follows [@Gorishnyi1], but uses Mamba blocks instead of transformer blocks.
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