Tensors and Dynamic neural networks in Python with strong GPU acceleration

Deep Learning for humans

scikit-learn: machine learning in Python

A natural language interface for computers

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

Fast and memory-efficient exact attention

Mamba SSM architecture

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

Deep universal probabilistic programming with Python and PyTorch

High accuracy RAG for answering questions from scientific documents with citations

This is the development home of the workflow management system Snakemake. For general information, see

Official repository for the Boltz-1 biomolecular interaction model

Open source tools for computational pathology - Nature BME

Python library to handle Gene Ontology (GO) terms

Implementation of Alpha Fold 3 from the paper: "Accurate structure prediction of biomolecular interactions with AlphaFold3" in PyTorch

U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

This repository includes the official implementation of OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs.

A Python implementation of the DESeq2 pipeline for bulk RNA-seq DEA.

Simultaneous Nuclear Instance Segmentation and Classification in H&E Histology Images.

Contrast-agnostic segmentation of MRI scans

Tools for computational pathology

DSMIL: Dual-stream multiple instance learning networks for tumor detection in Whole Slide Image

Towards Generalist Biomedical AI

A vision-language foundation model for computational pathology - Nature Medicine

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…

A standardized Python API with necessary preprocessing, machine learning and explainability tools to facilitate graph-analytics in computational pathology.

HEST: Bringing Spatial Transcriptomics and Histopathology together - NeurIPS 2024 (Spotlight)

Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction - CVPR 2024

Combinatorial antibiotic generation