-
Zhejiang University
- Hangzhou
Highlights
- Pro
Stars
Pytorch-adaptation of GPU-accelerated StainTool's stain normalization algorithms
BiomedGPT: A Generalist Vision-Language Foundation Model for Diverse Biomedical Tasks
Local models support for Microsoft's graphrag using ollama (llama3, mistral, gemma2 phi3)- LLM & Embedding extraction
HEST: Bringing Spatial Transcriptomics and Histopathology together
[ECCV 2024] Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain Imaging
Official PyTorch implementation of Learning to (Learn at Test Time): RNNs with Expressive Hidden States
[NeurIPS 2023] MeZO: Fine-Tuning Language Models with Just Forward Passes. https://arxiv.org/abs/2305.17333
preprocessing tools for multi-modal 3D brain MRI
Datasets for skin image analysis
Open-ST: profile and analyze tissue transcriptomes in 3D with high resolution in your lab
Transcriptomics-guided Slide Representation Learning in Computational Pathology - CVPR 2024
Official repository for "AM-RADIO: Reduce All Domains Into One"
Prov-GigaPath: A whole-slide foundation model for digital pathology from real-world data
Code for ICML2020 paper - CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
A Latex style and template for paper preprints (based on NIPS style)
Towards a general-purpose foundation model for computational pathology - Nature Medicine
A vision-language foundation model for computational pathology - Nature Medicine
[CVPR 2024] Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to ex…
[ICLR 2024]Implementation of "Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction"
Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction - CVPR 2024
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection