lbwnb32

lbwnb32's Stars

• imperial-qore/COSCO

  [TPDS'21] COSCO: Container Orchestration using Co-Simulation and Gradient Based Optimization for Fog Computing Environments

  Language:Python7844

• Yu-Maryland/RESPECT

  RESPECT: Reinforcement Learning based Edge Scheduling on Pipelined Coral Edge TPUs (DAC'23)

  Language:Python9

• OpsPAI/awesome-AIOps

  A curated list of awesome academic researches and industrial materials about Artificial Intelligence for IT Operations (AIOps).

  19225

• 98k-bot/GAN-Assisted-Preference-Based-Learning

  A paper under AAAI-20 review

  Language:Python61

• ben-eysenbach/mnm

  Code to accompany the paper "Mismatched No More: Joint Model-Policy Optimization for Model-Based RL"

  Language:Jupyter Notebook202

• louaaron/GAN-Q-Learning

  Unofficial Implementation of GAN Q Learning https://arxiv.org/abs/1805.04874

  Language:Python4610

• xinshi-chen/GenerativeAdversarialUserModel

  Tensorflow implementation for "Generative Adversarial User Model forReinforcement Learning Based Recommendation System"

  Language:Python12930

• rushhan/Generative-Adversarial-User-Model-for-Reinforcement-Learning-Based-Recommendation-System-Pytorch

  Language:Python4015

• zergtant/pytorch-handbook

  pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

  Language:Jupyter Notebook20.1k5.4k

• GraphNAS/GraphNAS

  This directory contains code necessary to run the GraphNAS algorithm.

  Language:Python17038

• FC-Li/CloudSimPy

  CloudSimPy: Datacenter job scheduling simulation framework

  Language:Python21975

• pprp/SimpleCVPaperReading

  :smile:博客论文列表：分系列整理

  Language:JavaScript39149

• Lei-Kun/End-to-end-DRL-for-FJSP

  This is the official code of the publised paper 'A Multi-action Deep Reinforcement Learning Framework for Flexible Job-shop Scheduling Problem'

  Language:Python22754

• jolibrain/wheatley

  Next-generation scheduling problem solver based on GNNs and Reinforcement Learning

  Language:Python379

• wisherg/python_data_course

  python pandas pyecharts streamlit echarts

  Language:Jupyter Notebook22762

• zhongyuanzhao/distgcn

  Link Scheduling using Graph Neural Networks, IEEE TWC

  Language:Python307

• sjtu-marl/malib

  A parallel framework for population-based multi-agent reinforcement learning.

  Language:Python48659

• rhoowd/sched_net

  Language:Python8129

• pengguo318/MaDRLAM

  Multi-Agent Deep Reinforcement Learning for Task Offloading in GDMSs

  Language:Python6314

• Jacklinkk/Graph_CAVs

  The source code for our paper: Graph Reinforcement Learning Application to Co-operative Decision-Making in Mixed Autonomy Traffic: Framework, Survey, and Challenges. This code is developed based on our previous repository TorchGRL.

  Language:Python545

• neunms/Reinforcement-learning-on-graphs-A-survey

  This collection of papers can be used to summarize research about graph reinforcement learning for the convenience of researchers.

  14221

• AccumulateMore/CV

  ✔（已完结）最全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】

  Language:Jupyter Notebook5.3k704

• IBM/tensorflow-kubernetes-art-classification

  Train a TensorFlow model on Kubernetes to recognize art culture based on the collection from the Metropolitan Museum of Art

  Language:Python6035

• Juntongkuki/DSFNet

  Language:Python51

• marrlab/InstantDL

  InstantDL: An easy and convenient deep learning pipeline for image segmentation and classification

  Language:Python408

• ertis-research/kafka-ml

  Kafka-ML: connecting the data stream with ML/AI frameworks (now TensorFlow and PyTorch!)

  Language:Python16224

• YuemingJin/TMRNet

  [TMI'2021] Temporal Memory Relation Network for Workflow Recognition from Surgical Video

  Language:Python5811

• mhaut/cloud-dnn-HSI

  Cloud Deep Networks for Hyperspectral Image Analysis

  Language:Scala63

• Vooban/Smoothly-Blend-Image-Patches

  Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.

  Language:Python36089

• sum1lim/sea_ice_remote_sensing

  Deep Learning models for Sea Ice Concentration classification generated from the architectures of Neural Network, 1D-CNN and concatenation of the two.

  Language:Python153