Training code for TabDPT: Scaling Tabular Foundation Models on Real Data

A comprehensive toolkit and benchmark for tabular data learning, featuring 35+ deep methods, more than 10 classical methods, and 300 diverse tabular datasets.

Inference code for "TabDPT: Scaling Tabular Foundation Models on Real Data"

Codebase accompanying the paper "Diagnosing and Fixing Manifold Overfitting in Deep Generative Models"

Codebase for evaluation of deep generative models as presented in Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models

Code for the NeurIPS'21 paper "Rectangular Flows for Manifold Learning"

PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows

Pytorch implementation of Localised Generative Flows

Keras implementation of a Variational Auto Encoder with a Concrete Latent Distribution

Pytorch implementation of Wasserstein GANs with Gradient Penalty