sdv-dev / CTGAN

#计算机科学#Synthetic data generation for tabular data

翻译 - 表格、关系和时间序列数据的合成数据生成。

#计算机科学#A library to model multivariate data using copulas.

Generative adversarial training for generating synthetic tabular data.

大模型Grok-1开源

Generative adversarial training for generating synthetic tabular data.

tableGAN is a synthetic data generation technique (Data Synthesis based on Generative Adversarial Networks paper) based on Generative Adversarial Network architecture (DCGAN).

#计算机科学#A PyTorch reimplementation of the paper Free-Form Image Inpainting with Gated Convolution (DeepFill v2) (https://arxiv.org/abs/1806.03589)

Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN

A framework for Claude Opus to intelligently orchestrate subagents.

#计算机科学#Official Implementation of ChromaGAN: An Adversarial Approach for Picture Colorization

#计算机科学#Lightning ⚡️ fast forecasting with statistical and econometric models.

#计算机科学#59 篇深度学习论文的实现，并带有详细注释。包括 transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 强化学习 (ppo, dqn), capsnet, distillation, ... 🧠

DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral

翻译 - 具有上下文注意和门控卷积的DeepFill v1 / v2，CVPR 2018和ICCV 2019 Oral

#计算机科学#A list of all named GANs!

翻译 - 所有已命名GAN的列表！

#计算机科学#A repository for explaining feature attributions and feature interactions in deep neural networks.

Official implementation of the paper "Double-DIP: Unsupervised Image Decomposition via Coupled Deep-Image-Priors"

翻译 - 论文“ Double-DIP：通过耦合深图像先验的无监督图像分解”的正式实施

PyTorch Implement of Context Encoders: Feature Learning by Inpainting

#计算机科学#[ICML 2023] The official implementation of the paper "TabDDPM: Modelling Tabular Data with Diffusion Models"