Official git for "CTAB-GAN: Effective Table Data Synthesizing"

Related tags

Deep LearningCTAB-GAN
Overview

CTAB-GAN

This is the official git paper CTAB-GAN: Effective Table Data Synthesizing. The paper is published on Asian Conference on Machine Learning (ACML 2021), please check our pdf on PMLR website for our newest version of paper, it adds more content on time consumption analysis of training CTAB-GAN. If you have any question, please contact [email protected] for more information.

Example

Experiment_Script_Adult.ipynb is an example notebook for training CTAB-GAN with Adult dataset. The dataset is alread under Real_Datasets folder. The evaluation code is also provided.

For large dataset

If your dataset has large number of column, you may encounter the problem that our currnet code cannot encode all of your data since CTAB-GAN will wrap the encoded data into an image-like format. What you can do is changing the line 341 and 348 in model/synthesizer/ctabgan_synthesizer.py. The number in the slide list

sides = [4, 8, 16, 24, 32]

is the side size of image. You can enlarge the list to [4, 8, 16, 24, 32, 64] or [4, 8, 16, 24, 32, 64, 128] for accepting larger dataset.

Bibtex

To cite this paper, you could use this bibtex

@InProceedings{zhao21,
  title = 	 {CTAB-GAN: Effective Table Data Synthesizing},
  author =       {Zhao, Zilong and Kunar, Aditya and Birke, Robert and Chen, Lydia Y.},
  booktitle = 	 {Proceedings of The 13th Asian Conference on Machine Learning},
  pages = 	 {97--112},
  year = 	 {2021},
  editor = 	 {Balasubramanian, Vineeth N. and Tsang, Ivor},
  volume = 	 {157},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {17--19 Nov},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v157/zhao21a/zhao21a.pdf},
  url = 	 {https://proceedings.mlr.press/v157/zhao21a.html}
}


[NeurIPS-2021] Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data

MosaicKD Code for NeurIPS-21 paper "Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data" 1. Motivation Natural images share common l

ZJU-VIPA 37 Nov 10, 2022
Code for paper "Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs"

This is the codebase for the paper: Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs Directory Structur

Peter Hase 19 Aug 21, 2022
Video-face-extractor - Video face extractor with Python

Python face extractor Setup Create the srcvideos and faces directories Put your

2 Feb 03, 2022
A Lightweight Hyperparameter Optimization Tool 🚀

Lightweight Hyperparameter Optimization 🚀 The mle-hyperopt package provides a simple and intuitive API for hyperparameter optimization of your Machin

136 Jan 08, 2023
A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"

SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th

Zekarias Tilahun 24 Jun 21, 2022
Implement of "Training deep neural networks via direct loss minimization" in PyTorch for 0-1 loss

This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe

Cuong Nguyen 1 Jan 18, 2022
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor

Ozan Oktay 1.6k Dec 30, 2022
The repository offers the official implementation of our BMVC 2021 paper in PyTorch.

CrossMLP Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation Bin Ren1, Hao Tang2, Nicu Sebe1. 1University of Trento, Italy, 2ETH, Switzerla

Bingoren 16 Jul 27, 2022
Object Detection using YOLO from PyImageSearch

Object Detection using YOLO from PyImageSearch By applying object detection, you’ll not only be able to determine what is in an image, but also where

Mohamed NIANG 1 Feb 09, 2022
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering

Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering

Meng Liu 2 Jul 19, 2022
A Game-Theoretic Perspective on Risk-Sensitive Reinforcement Learning

Officile code repository for "A Game-Theoretic Perspective on Risk-Sensitive Reinforcement Learning"

Mathieu Godbout 1 Nov 19, 2021
EssentialMC2 Video Understanding

EssentialMC2 Introduction EssentialMC2 is a complete system to solve video understanding tasks including MHRL(representation learning), MECR2( relatio

Alibaba 106 Dec 11, 2022
This project uses Template Matching technique for object detecting by detection of template image over base image.

Object Detection Project Using OpenCV This project uses Template Matching technique for object detecting by detection the template image over base ima

Pratham Bhatnagar 7 May 29, 2022
PlenOctrees: NeRF-SH Training & Conversion

PlenOctrees Official Repo: NeRF-SH training and conversion This repository contains code to train NeRF-SH and to extract the PlenOctree, constituting

Alex Yu 323 Dec 29, 2022
Explaining Hyperparameter Optimization via PDPs

Explaining Hyperparameter Optimization via PDPs This repository gives access to an implementation of the methods presented in the paper submission “Ex

2 Nov 16, 2022
An implementation of the [Hierarchical (Sig-Wasserstein) GAN] algorithm for large dimensional Time Series Generation

Hierarchical GAN for large dimensional financial market data Implementation This repository is an implementation of the [Hierarchical (Sig-Wasserstein

11 Nov 29, 2022
smc.covid is an R package related to the paper A sequential Monte Carlo approach to estimate a time varying reproduction number in infectious disease models: the COVID-19 case by Storvik et al

smc.covid smc.covid is an R package related to the paper A sequential Monte Carlo approach to estimate a time varying reproduction number in infectiou

0 Oct 15, 2021
Reproduces ResNet-V3 with pytorch

ResNeXt.pytorch Reproduces ResNet-V3 (Aggregated Residual Transformations for Deep Neural Networks) with pytorch. Tried on pytorch 1.6 Trains on Cifar

Pau Rodriguez 481 Dec 23, 2022
Codebase for BMVC 2021 paper "Text Based Person Search with Limited Data"

Text Based Person Search with Limited Data This is the codebase for our BMVC 2021 paper. Please bear with me refactoring this codebase after CVPR dead

Xiao Han 33 Nov 24, 2022
GRF: Learning a General Radiance Field for 3D Representation and Rendering

GRF: Learning a General Radiance Field for 3D Representation and Rendering [Paper] [Video] GRF: Learning a General Radiance Field for 3D Representatio

Alex Trevithick 243 Dec 29, 2022