Stars
this repository is about The 5th JITTOR Artificial Intelligence Challenge Track 1: Intelligent Screening and Grading of Ultrasound Images
A Collection of Variational Autoencoders (VAE) in PyTorch.
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
[NeurIPS 2025] DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge
A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
A Haskell library for converting LaTeX math to MathML.
Segment Anything Model for Medical Image Segmentation: Open-Source Project Summary
Attachment Manager for Zotero
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Pytorch Implementation (unofficial) of the paper "Mean Flows for One-step Generative Modeling" by Geng et al.
Everything integration for the Windows taskbar.
An open source AMS feeding system designed based on open source data for Bambu Lab A1 mini printers
Tiny AutoEncoder for Stable Diffusion (and other image models)
A PyTorch library for implementing flow matching algorithms, featuring continuous and discrete flow matching implementations. It includes practical examples for both text and image modalities.
Fast and differentiable MS-SSIM and SSIM for pytorch.
MedSora: Optical Flow Representation Alignment Mamba Diffusion Model for Medical Video Generation (Official PyTorch Implementation)
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
[MICCAI 2023] DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification
Shortcut flow matching Pytorch implementation
A set of TFDS dataset builders for common datasets
source code for "ROBIN: Robust and Invisible Watermarks for Diffusion Models with Adversarial Optimization"
Official implementation of NeurIPS'24 paper "Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models". This work adversarially unlearns the text encoder to enh…