About
The generation of tabular data by any means possible.
Benchmarks
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
|---|---|---|---|---|---|---|
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Datasets
Greatest papers with code
Improved Training of Wasserstein GANs
NeurIPS 2017
• eriklindernoren/PyTorch-GAN
• 
Generative Adversarial Networks (GANs) are powerful generative models, but suffer from training instability.
Ranked #2 on
Image Generation
on CAT 256x256
Wasserstein GAN
• eriklindernoren/PyTorch-GAN
•
We introduce a new algorithm named WGAN, an alternative to traditional GAN training.
Synthetic QA Corpora Generation with Roundtrip Consistency
ACL 2019
• patil-suraj/question_generation
•
We introduce a novel method of generating synthetic question answering corpora by combining models of question generation and answer extraction, and by filtering the results to ensure roundtrip consistency.
QUESTION ANSWERING QUESTION GENERATION SYNTHETIC DATA GENERATION
Burst Denoising with Kernel Prediction Networks
CVPR 2018
• google/burst-denoising
• 
We present a technique for jointly denoising bursts of images taken from a handheld camera.
Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions
By shedding light on the promise and challenges, we hope our work can rekindle the conversation on workflows for data sharing.
A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing
ICCV 2017
• fqnchina/CEILNet
• 
This paper proposes a deep neural network structure that exploits edge information in addressing representative low-level vision tasks such as layer separation and image filtering.
IMAGE SMOOTHING REFLECTION REMOVAL SYNTHETIC DATA GENERATION
Scenic: A Language for Scenario Specification and Data Generation
We design a domain-specific language, Scenic, for describing scenarios that are distributions over scenes and the behaviors of their agents over time.
Scenic: A Language for Scenario Specification and Scene Generation
We propose a new probabilistic programming language for the design and analysis of perception systems, especially those based on machine learning.
PROBABILISTIC PROGRAMMING SCENE GENERATION SYNTHETIC DATA GENERATION
UnrealROX: An eXtremely Photorealistic Virtual Reality Environment for Robotics Simulations and Synthetic Data Generation
Gathering and annotating that sheer amount of data in the real world is a time-consuming and error-prone task.
DEPTH ESTIMATION OBJECT DETECTION SEMANTIC SEGMENTATION SYNTHETIC DATA GENERATION
Tabular Transformers for Modeling Multivariate Time Series
• IBM/TabFormer
•
This results in two architectures for tabular time series: one for learning representations that is analogous to BERT and can be pre-trained end-to-end and used in downstream tasks, and one that is akin to GPT and can be used for generation of realistic synthetic tabular sequences.
FRAUD DETECTION HIERARCHICAL STRUCTURE SYNTHETIC DATA GENERATION TIME SERIES