A latent text-to-image diffusion model

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

《统计学习方法》的代码实现

Instruct-tune LLaMA on consumer hardware

《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

High-Resolution Image Synthesis with Latent Diffusion Models

数据科学的笔记以及资料搜集

Using Low-rank adaptation to quickly fine-tune diffusion models.

PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) by way of Textual Inversion (https://arxiv.org/abs/2208.01618) for Stable Diffusion (https://arxiv.org/abs/2112.10752). Tweaks focuse…

Optimized Stable Diffusion modified to run on lower GPU VRAM

MIMIC Code Repository: Code shared by the research community for the MIMIC family of databases

Unofficial implementation of "Prompt-to-Prompt Image Editing with Cross Attention Control" with Stable Diffusion

TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.

MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications

Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)

Code, documentation, and discussion around the MIMIC-CXR database

[NeurIPS'22] Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning

[ICML 2020] Continuously Indexed Domain Adaptation

Reinforcement Learning based 'Learning' of Dynamic Sepsis Treatment Strategies

My personal research notebook with notes, tutorials, and resources written in Jupyterbook.

Exploring variational-autoencoder-based semantic segmentation for analyzing CT-scans.

Lectures, Papers, Reviews, and Implementations

Style Separation and Synthesis via Generative Adversarial Networks