Popular GitHub Repositories for Endothelial Cells

Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.

AI-powered Jupyter Notebook — use local AI to generate and edit code cells, automatically fix errors, and chat with your data

The collaborative spreadsheet for AI. Chain cells into powerful pipelines, experiment with prompts and models, and evaluate LLM responses in real-time. Work together seamlessly to build and iterate on AI applications.

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

Using multi-agent Deep Q Learning with LSTM cells (DRQN) to train multiple users in cognitive radio to learn to share scarce resource (channels) equally without communication

A python package for simulating movement and spatial cell types (e.g. place cells, grid cells) in continuous environments.

Language Modeling

Code for Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells, CVPR '19

Machine learning approach of automatic identification and counting of blood cells (RBC, WBC, and Platelet) with KNN and IOU based verification.

This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.

Learning cell communication from spatial graphs of cells

a cutting-edge cell segmentation model specifically designed for single-molecule resolved spatial omics datasets. It addresses the challenge of accurately segmenting individual cells in complex imaging datasets, leveraging a unique approach based on graph neural networks (GNNs).

GPT JupterLab is a JupyterLab extension to use OpenAI’s GPT models for text and code completion on your notebook cells.

Sentiment Analysis using LSTM cells on Recurrent Networks. GloVe word embeddings were used for vector representation of words. Amazon Product Reviews were used as Dataset.

A Simple Automatic Speech Recognition (ASR) Model in Tensorflow, which only needs to focus on Deep Neural Network. It's easy to test popular cells (most are LSTM and its variants) and models (unidirectioanl RNN, bidirectional RNN, ResNet and so on). Moreover, you are welcome to play with self-defined cells or models.

Yeezy Taught Me Text Generation. Training next character predictions RNN LSTM model with user input text corpus

Keras (Tensorflow) code for the manuscript 'DenseUNets with feedback non-local attention for the segmentation of specular images of the corneal endothelium with Fuchs dystrophy'

Adaptive Computation Time (Graves, 2016, arXiv:1603.08983) wrapper for TensorFlow RNN cells.

Compare Naive Bayes, SVM, XGBoost, Bagging, AdaBoost, K-Nearest Neighbors, Random Forests for classification of Malaria Cells

A CNN in PyTorch that counts cells in images