Papers with Code 아카이브

Tabular Data Generation

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전체 기법전체 데이터셋

하위 태스크

0

평가표

6

보존된 평가 기록

36

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/sassoftware/dpmm

공식 코드

dpmm: Differentially Private Marginal Models, a Library for Synthetic Tabular Data Generation

https://github.com/sattarov/FinDiff

공식 코드

FinDiff: Diffusion Models for Financial Tabular Data Generation

https://github.com/sattarov/fedtabdiff

공식 코드

FedTabDiff: Federated Learning of Diffusion Probabilistic Models for Synthetic Mixed-Type Tabular Data Generation

https://github.com/seharanul17/synthetic-tabular-LLM

공식 코드

EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Models

https://github.com/shengzhexu/permutation-aided-fine-tuning

공식 코드

Are LLMs Naturally Good at Synthetic Tabular Data Generation?

https://github.com/tejuafonja/dp-2stage

공식 코드

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators

https://github.com/vanderschaarlab/data-centric-synthetic-data

공식 코드

Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark

https://github.com/vikram2000b/tabsyndex

공식 코드

TabSynDex: A Universal Metric for Robust Evaluation of Synthetic Tabular Data

https://github.com/vkinakh/binary-diffusion-tabular

공식 코드

Tabular Data Generation using Binary Diffusion

https://github.com/zhangtp1996/taptap

공식 코드

Generative Table Pre-training Empowers Models for Tabular Prediction

https://github.com/zhao-zilong/tabula

공식 코드

TabuLa: Harnessing Language Models for Tabular Data Synthesis

https://github.com/dssg/aequitas

Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation

https://github.com/juliecious/ctgan

Modeling Tabular data using Conditional GAN

https://github.com/lvyufeng/CTGAN-MindSpore

Modeling Tabular data using Conditional GAN

https://github.com/mostly-ai/mostlyai

TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data

https://github.com/oregonpillow/ctgan-server-cli

Modeling Tabular data using Conditional GAN

https://github.com/saha0073/GAN-VAE-to-generate-Synthetic-Tabular-Data

Modeling Tabular data using Conditional GAN

https://github.com/sdv-dev/CTGAN

Modeling Tabular data using Conditional GAN

https://github.com/sebhaan/TabPFGen

TabPFGen -- Tabular Data Generation with TabPFN

https://github.com/team-tud/ctab-gan

TabuLa: Harnessing Language Models for Tabular Data Synthesis

https://github.com/team-tud/ctab-gan-plus

TabuLa: Harnessing Language Models for Tabular Data Synthesis

https://github.com/ydataai/ydata-synthetic/tree/dev/src/ydata_synthetic/synthesizers/regular/ctgan

Modeling Tabular data using Conditional GAN

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.