RecTable: Fast Modeling Tabular Data with Rectified Flow
Score-based or diffusion models generate high-quality tabular data,
surpassing GAN-based and VAE-based models. However, these methods require
substantial training time. In this paper, we introduce RecTable, which uses the
rectified flow modeling, applied in such as text-to-image generation and
text-to-video generation. RecTable features a simple architecture consisting of
a few stacked gated linear unit blocks. Additionally, our training strategies
are also simple, incorporating a mixed-type noise distribution and a
logit-normal timestep distribution. Our experiments demonstrate that RecTable
achieves competitive performance compared to the several state-of-the-art
diffusion and score-based models while reducing the required training time. Our
code is available at https://github.com/fmp453/rectable.
67e5574421895bd1f38b73be
Masane Fuchi
claimed_verified
2025-03-27T14:25:10.082Z
638f03e5f9fb22b5a073db1b
/avatars/8b4ae473175e961d0340a6901dabcf29.svg
Masane Fuchi
user
fmuuly
67e5574421895bd1f38b73bf
Tomohiro Takagi
RecTable: Fast Modeling Tabular Data with Rectified Flow
Score-based or diffusion models generate high-quality tabular data,
surpassing GAN-based and VAE-based models. However, these methods require
substantial training time. In this paper, we introduce RecTable, which uses the
rectified flow modeling, applied in such as text-to-image generation and
text-to-video generation. RecTable features a simple architecture consisting of
a few stacked gated linear unit blocks. Additionally, our training strategies
are also simple, incorporating a mixed-type noise distribution and a
logit-normal timestep distribution. Our experiments demonstrate that RecTable
achieves competitive performance compared to the several state-of-the-art
diffusion and score-based models while reducing the required training time. Our
code is available at https://github.com/fmp453/rectable.
RecTable, a diffusion model using rectified flow modeling with a simple architecture and training strategies, generates high-quality tabular data more efficiently than existing models.
score-based models diffusion models GAN-based models VAE-based models rectified flow modeling gated linear unit blocks mixed-type noise distribution logit-normal timestep distribution