Stars
The implementations for CVPR 2025 paper "Learning Heterogeneous Tissues with Mixture of Experts for Gigapixel Whole Slide Images".
Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing
SEQUOIA: Digital profiling of cancer transcriptomes with grouped vision attention
Deep learning based method called hist2RNA to predict the expression of genes using digital images of stained tissue samples
Train a model to predict gene expression from histology slides.
This repository will host a (continously updated) list of various deep learning methods used in different stages of spatial transcriptomics analysis.
QuST: QuPath Extension for Integrative Whole Slide Image and Spatial Transcriptomics Analysis
An ultra-fast all-in-one FASTQ preprocessor (QC/adapters/trimming/filtering/splitting/merging...)
Burrow-Wheeler Aligner for short-read alignment (see minimap2 for long-read alignment)
A small package to create visualizations of PyTorch execution graphs
A vision language model for gigapixel whole slide images in histopathology
BiomedParse: A Foundation Model for Joint Segmentation, Detection, and Recognition of Biomedical Objects Across Nine Modalities
On-device AI across mobile, embedded and edge for PyTorch
마틴 파울러 님의 리팩토링을 읽고 정리한 레파지토리입니다.
VILA is a family of state-of-the-art vision language models (VLMs) for diverse multimodal AI tasks across the edge, data center, and cloud.
Examples of libtorch, which is C++ front end of PyTorch
1000 images, one per image-net class. For easy visualization/exploration of classes.
C++ Implementation of PyTorch Tutorials for Everyone
pytorch python vs cpp LibTorch benchmark comparison using ResNet Training, and Inference
A tensorflow implementation of Knowledge Graph Convolutional Networks