Kirito-E2D

Kirito-E2D's Stars

• buds-lab/energystar-plus-plus

  Using Gradient Boosting Trees and Explainable ML for Commericial Building Benchmarking

  Language:HTML82

• Kirito-E2D/Building-data

  507 buildings from the-building-data-genome-project

  Language:Python2

• Kirito-E2D/Predict-the-future

  long short term memory

  Language:Python5

• Kirito-E2D/Federated-learning-based-prediction

  use federated learning to predict building energy consumption

  Language:Jupyter Notebook143

• kimhc6028/soft-decision-tree

  pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"

  Language:Python28259

• intelligent-environments-lab/CityLearn

  Official reinforcement learning environment for demand response and load shaping

  Language:Python462167

• buds-lab/the-building-data-genome-project

  A collection of non-residential buildings for performance analysis and algorithm benchmarking

  Language:Jupyter Notebook18359

• tao-shen/Federated-Learning-FAQ

  18539

• wangshusen/DeepLearning

  Language:TeX3.6k821

• PaperStrange/AIProjectManger

  Aimed at the optimization of file structure to facilitate rapid construction of project prototypes (in processing)

  Language:Jupyter Notebook3

• PaperStrange/ResearchRecorder

  A recorder as well as a copy of records during the scientific researches (in processing)

  2