From f15d99ff3dc5094750e1c14ee6c3bf05744f0d1b Mon Sep 17 00:00:00 2001
From: Christoph Weisser <50968720+ChrisW09@users.noreply.github.com>
Date: Sat, 25 May 2024 15:18:54 +0200
Subject: [PATCH] Update paper.md

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 date: 22 April 2024
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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.