Popular GitHub Repositories for Nature

PyTorch and TensorFlow implementation of NCP, LTC, and CfC wired neural models

[Nature Reviews Bioengineering?] Application of Large Language Models in Medicine. A curated list of practical guide resources of Medical LLMs (Medical LLMs Tree, Tables, and Papers)

Omniscient Knowledge Graph for Artificial Intelligence

基于Pytorch和torchtext的自然语言处理深度学习框架。

Towards a general-purpose foundation model for computational pathology - Nature Medicine

EvoloPy toolbox provides classical and recent nature-inspired metaheuristic for the global optimization.

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 extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.

Draw flowchart, sequence diagram, class diagram, user journey, gantt, C4C diagram with nature language.

[ICCV 2021] Aligning Latent and Image Spaces to Connect the Unconnectable

A deep reinforcement learning (DRL) based approach for spatial layout of land use and roads in urban communities. (Nature Computational Science)

Deep Learning Inferred Multiplex ImmunoFluorescence for IHC Image Quantification (https://deepliif.org) [Nature Machine Intelligence'22, CVPR'22, MICCAI'23, Histopathology'23, MICCAI'24]

PocketGen (Nature Machine Intelligence 24): Generating Full-Atom Ligand-Binding Protein Pockets

A tensorflow.keras generative neural network for de novo drug design, first-authored in Nature Machine Intelligence while working at AstraZeneca.

Regression Transformer (2023; Nature Machine Intelligence)

Image Acceptable Alpaca (Image-Text Chat AI).

Using DUCK-Net for polyp image segmentation. ( Nature Scientific Reports 2023 )

[Nature Machine Intelligence 2024] Code and evaluation repository for the paper

Successfully developed a machine learning model which can predict whether an online review is fraudulent or not. The main idea used to detect the fake nature of reviews is that the review should be computer generated through unfair means. If the review is created manually, then it is considered legal and original.

Nature of Code - Autonomous Agents examples in 3D