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NeuroIDSS's Projects

gamegan_code icon gamegan_code

Learning to Simulate Dynamic Environments with GameGAN (CVPR 2020)

gansnroses icon gansnroses

Official PyTorch repo for GAN's N' Roses. Diverse im2im and vid2vid selfie to anime translation.

gd32-rs icon gd32-rs

Embedded Rust device crates for GD32 microcontrollers

ghdl icon ghdl

VHDL 2008/93/87 simulator

gnatsd icon gnatsd

High-Performance server for NATS, the cloud native messaging system.

godot icon godot

Godot Engine – Multi-platform 2D and 3D game engine

gpt-2 icon gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

gpt-neo icon gpt-neo

An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

gpt-neox icon gpt-neox

An implementation of model parallel GPT-3-like models on GPUs, based on the DeepSpeed library. Designed to be able to train models in the hundreds of billions of parameters or larger.

grafana icon grafana

The tool for beautiful monitoring and metric analytics & dashboards for Graphite, InfluxDB & Prometheus & More

graphpype icon graphpype

Neuropycon package of functions for electrophysiology analysis, can be used from ephypype and nipype

gym icon gym

A toolkit for developing and comparing reinforcement learning algorithms.

h icon h

Annotate with anyone, anywhere.

handson-ml2 icon handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

har-cnn-keras icon har-cnn-keras

Human Activity Recognition Using Convolutional Neural Network in Keras

hassio icon hassio

:house_with_garden: First private cloud supervisor for home automation

heg_esp32 icon heg_esp32

HEGduino with ESP32: Hemoencephalography meets highly affordable IoT!

hhvm icon hhvm

A virtual machine designed for executing programs written in Hack and PHP.

hnn icon hnn

The Human Neocortical Neurosolver (HNN) is a software tool that gives researchers/clinicians the ability to develop/test hypotheses on circuit mechanisms underlying EEG/MEG data.

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