Papers with Code 아카이브
Synthetic Data Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 2
- 보존된 평가 기록
- 4
The generation of tabular data by any means possible.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mcclow12/wgan-gp-pytorch
https://github.com/michael13162/DoodleGAN
https://github.com/mindspore-ai/models/blob/master/research/cv/wgan
https://github.com/mitscha/dplc
https://github.com/mostly-ai/mostlyai
https://github.com/nannau/DoWnGAN
https://github.com/natuan310/scale-recurrent-network-images-deblurring
https://github.com/nicobernasconi/specgan
https://github.com/nindoumon/SoftAdapt
SoftAdapt: Techniques for Adaptive Loss Weighting of Neural Networks with Multi-Part Loss Functions
https://github.com/njucckevin/seeclick
OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesis
https://github.com/open-mmlab/mmgeneration
https://github.com/owl-project/ViSII
NViSII: A Scriptable Tool for Photorealistic Image Generation
https://github.com/patil-suraj/question_generation
https://github.com/pminhtam/KPN_attention
https://github.com/polmonroig/faceGAN
https://github.com/pumperknickle/DoppelGANgerIOT
Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions
https://github.com/qnduan/wgan-scrna
https://github.com/raylyh/misgan-reimplementation
https://github.com/rkem1542/EDSR-pytorch
https://github.com/rmyhovych/wgan
https://github.com/safwankdb/Wasserstein-GAN
https://github.com/sanghyun-son/EDSR-PyTorch
https://github.com/seanmullery/iWGAN
https://github.com/shahbuland/basic-gans
https://github.com/shekkizh/WassersteinGAN.tensorflow
https://github.com/snow-mn/GAN-INT-CLS
https://github.com/spandan2/Wgan-GP_cats
https://github.com/t0nberryking/DCGAN256
https://github.com/tSchlegl/f-AnoGAN
https://github.com/tensorpack/tensorpack/tree/master/examples/GAN
https://github.com/terranceliu/iterative-dp
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods
https://github.com/thstkdgus35/EDSR-PyTorch
https://github.com/triple7/Keras-WGAN-RGB-128x128
https://github.com/u7javed/Conditional-WGAN-GP
https://github.com/unicredit/ganzo
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.