most citedOne Transformer for All Time Series: Representing and Training with Time-Dependent Heterogeneous Tabular Data

3 citations · 3 across the 2 of their papers we have counts for

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cs.LG2025

Diffusion Transformers for Tabular Data Time Series Generation

Fabrizio Garuti, Enver Sangineto, Simone Luetto +2

Tabular data generation has recently attracted a growing interest due to its different application scenarios. However, generating time series of tabular data, where each element of…

cs.LG2023★ 3 cited

One Transformer for All Time Series: Representing and Training with Time-Dependent Heterogeneous Tabular Data

Simone Luetto, Fabrizio Garuti, Enver Sangineto +2

There is a recent growing interest in applying Deep Learning techniques to tabular data, in order to replicate the success of other Artificial Intelligence areas in this structured…