Gradient Ascent Pulse Engineering in Julia
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Updated
Jun 11, 2024 - Julia
Gradient Ascent Pulse Engineering in Julia
NYUS.2 is an auto machine learning-empowered prediction model for grapevine freezing tolerance
A page builder for laravel that works in a very simple and easy way, by default onix uses tailwind css, but can be easy change to your custom css.
A full-featured, production ready, and easy to understand API boilerplate for the Grape framework.
🍇 A C++ library for parallel graph processing (GRAPE) 🍇
SAML Authentication proxy for Discourse SSO
Doorkeeper is an OAuth 2 provider for Ruby on Rails / Grape.
Julia Framework for Quantum Dynamics and Control
Dynamic Gradients for Quantum Control
This study aims to develop a deep learning-based image classifier to detect diseases of grape crops in agriculture. This study will develop convolutional neural network (CNN) models for the image classification of grape leaf diseases using the VGG16 architecture.
Use jsonapi-serializer with Grape
Building an API with Ruby using TDD, DDD, Clean Architecture, Design Patterns and SOLID principles
A reusable Grape JWT authentication concern
Add a description, image, and links to the grape topic page so that developers can more easily learn about it.
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