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The generation of tabular data by any means possible.

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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.

CONDITIONAL IMAGE GENERATION SYNTHETIC DATA GENERATION

Wasserstein GAN

26 Jan 2017eriklindernoren/PyTorch-GAN

We introduce a new algorithm named WGAN, an alternative to traditional GAN training.

IMAGE GENERATION SYNTHETIC DATA GENERATION

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.

DENOISING SYNTHETIC DATA GENERATION

Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions

30 Sep 2019fjxmlzn/DoppelGANger

By shedding light on the promise and challenges, we hope our work can rekindle the conversation on workflows for data sharing.

SYNTHETIC DATA GENERATION TIME SERIES

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

13 Oct 2020BerkeleyLearnVerify/Scenic

We design a domain-specific language, Scenic, for describing scenarios that are distributions over scenes and the behaviors of their agents over time.

PROBABILISTIC PROGRAMMING SYNTHETIC DATA GENERATION

Scenic: A Language for Scenario Specification and Scene Generation

25 Sep 2018BerkeleyLearnVerify/Scenic

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

Tabular Transformers for Modeling Multivariate Time Series

3 Nov 2020IBM/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