Popular GitHub Repositories for Dynamic Scheduling

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Convert ebooks to audiobooks with chapters and metadata using dynamic AI models and voice cloning. Supports 1,107+ languages!

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution

A Tensorflow implementation of CapsNet(Capsules Net) in paper Dynamic Routing Between Capsules

XIAOJUSURVEY is an enterprises form builder and analytics platform that allows users to create questionnaires, exams, polls, quizzes, and analyze data online.

AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.

[CVPR 2024] 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering

AGiXT is a dynamic AI Agent Automation Platform that seamlessly orchestrates instruction management and complex task execution across diverse AI providers. Combining adaptive memory, smart features, and a versatile plugin system, AGiXT delivers efficient and comprehensive AI solutions.

The machine learning toolkit for time series analysis in Python

NMA Computational Neuroscience course

Resource scheduling and cluster management for AI

Speedy Wavenet generation using dynamic programming :zap:

A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".

Simulation of spiking neural networks (SNNs) using PyTorch.

A QoS-based scheduling system brings optimal layout and status to workloads such as microservices, web services, big data jobs, AI jobs, etc.

动态语义SLAM 目标检测+VSLAM+光流/多视角几何动态物体检测+octomap地图+目标数据库

The open source Solver AI for Java, Python and Kotlin to optimize scheduling and routing. Solve the vehicle routing problem, employee rostering, task assignment, maintenance scheduling and other planning problems.

Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.

An Industrial Graph Neural Network Framework