Repository for the electrical and ICT benchmark model developed in the ERIGrid 2.0 project.

Overview

Benchmark Model Electrical and ICT System

This repository contains the documentation, code, and models for the electrical and ICT benchmark model developed in the ERIGrid 2.0 project.

DOI

The repository is structured into two folders:

  • The folder Implementation Files includes model and code Files
  • The folder PreCISE Documentation contains the description of the model according to the PreCISE framework
    • The different subfolders are indexed according to the PreCISE template

Funding Acknowledgement

European Flag The development of Benchmark Electrical and ICT Model has been supported by the ERIGrid 2.0 project of the H2020 Programme under Grant Agreement No. 870620

You might also like...
Easily benchmark PyTorch model FLOPs, latency, throughput, max allocated memory and energy consumption

⏱ pytorch-benchmark Easily benchmark model inference FLOPs, latency, throughput, max allocated memory and energy consumption Install pip install pytor

Repository for Traffic Accident Benchmark for Causality Recognition (ECCV 2020)
Repository for Traffic Accident Benchmark for Causality Recognition (ECCV 2020)

Causality In Traffic Accident (Under Construction) Repository for Traffic Accident Benchmark for Causality Recognition (ECCV 2020) Overview Data Prepa

Repository for the Bias Benchmark for QA dataset.

BBQ Repository for the Bias Benchmark for QA dataset. Authors: Alicia Parrish, Angelica Chen, Nikita Nangia, Vishakh Padmakumar, Jason Phang, Jana Tho

Baseline model for
Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020)

GraspNet Baseline Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020). [paper] [dataset] [API] [do

[IJCAI-2021] A benchmark of data-free knowledge distillation from paper
[IJCAI-2021] A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation"

DataFree A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation" Authors: Gongfa

Ultra-lightweight human body posture key point CNN model. ModelSize:2.3MB  HUAWEI P40 NCNN benchmark: 6ms/img,
Ultra-lightweight human body posture key point CNN model. ModelSize:2.3MB HUAWEI P40 NCNN benchmark: 6ms/img,

Ultralight-SimplePose Support NCNN mobile terminal deployment Based on MXNET(=1.5.1) GLUON(=0.7.0) framework Top-down strategy: The input image is t

General Vision Benchmark, a project from OpenGVLab

Introduction We build GV-B(General Vision Benchmark) on Classification, Detection, Segmentation and Depth Estimation including 26 datasets for model e

Step by Step on how to create an vision recognition model using LOBE.ai, export the model and run the model in an Azure Function
Step by Step on how to create an vision recognition model using LOBE.ai, export the model and run the model in an Azure Function

Step by Step on how to create an vision recognition model using LOBE.ai, export the model and run the model in an Azure Function

PassAPI is a password generator in hash format and fully developed in Python, with the aim of teaching how to handle and build
PassAPI is a password generator in hash format and fully developed in Python, with the aim of teaching how to handle and build

simple, elegant and safe Introduction PassAPI is a password generator in hash format and fully developed in Python, with the aim of teaching how to ha

Releases(v1.0)
Owner
ERIGrid 2.0
European Research Infrastructure supporting Smart Grid and Smart Energy Systems Research, Technology Development, Validation and Roll Out – Second Edition
ERIGrid 2.0
[CVPR 21] Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2021.

Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting, CVPR 2021. Ayan Kumar Bhunia, Pinaki nath Chowdhury, Yongxin Yan

Ayan Kumar Bhunia 44 Dec 12, 2022
Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020.

RegNet Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020. Paper | Official Implementation RegNet offer a very

Vishal R 2 Feb 11, 2022
A Simplied Framework of GAN Inversion

Framework of GAN Inversion Introcuction You can implement your own inversion idea using our repo. We offer a full range of tuning settings (in hparams

Kangneng Zhou 13 Sep 27, 2022
End-To-End Crowdsourcing

End-To-End Crowdsourcing Comparison of traditional crowdsourcing approaches to a state-of-the-art end-to-end crowdsourcing approach LTNet on sentiment

Andreas Koch 1 Mar 06, 2022
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Apache MXNet (incubating) for Deep Learning Master Docs License Apache MXNet (incubating) is a deep learning framework designed for both efficiency an

ROCm Software Platform 29 Nov 16, 2022
Objax Apache-2Objax (🥉19 · ⭐ 580) - Objax is a machine learning framework that provides an Object.. Apache-2 jax

Objax Tutorials | Install | Documentation | Philosophy This is not an officially supported Google product. Objax is an open source machine learning fr

Google 729 Jan 02, 2023
DCGAN LSGAN WGAN-GP DRAGAN PyTorch

Recommendation Our GAN based work for facial attribute editing - AttGAN. News 8 April 2019: We re-implement these GANs by Tensorflow 2! The old versio

Zhenliang He 408 Nov 30, 2022
PyTorch and Tensorflow functional model definitions

functional-zoo Model definitions and pretrained weights for PyTorch and Tensorflow PyTorch, unlike lua torch, has autograd in it's core, so using modu

Sergey Zagoruyko 590 Dec 22, 2022
Direct design of biquad filter cascades with deep learning by sampling random polynomials.

IIRNet Direct design of biquad filter cascades with deep learning by sampling random polynomials. Usage git clone https://github.com/csteinmetz1/IIRNe

Christian J. Steinmetz 55 Nov 02, 2022
The final project of "Applying AI to EHR Data" of "AI for Healthcare" nanodegree - Udacity.

Patient Selection for Diabetes Drug Testing Project Overview EHR data is becoming a key source of real-world evidence (RWE) for the pharmaceutical ind

Omar Laham 1 Jan 14, 2022
Improving Calibration for Long-Tailed Recognition (CVPR2021)

MiSLAS Improving Calibration for Long-Tailed Recognition Authors: Zhisheng Zhong, Jiequan Cui, Shu Liu, Jiaya Jia [arXiv] [slide] [BibTeX] Introductio

Jia Research Lab 116 Dec 20, 2022
DGN pymarl - Implementation of DGN on Pymarl, which could be trained by VDN or QMIX

This is the implementation of DGN on Pymarl, which could be trained by VDN or QM

4 Nov 23, 2022
Official Implementation of "Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras"

Multi Camera Pig Tracking Official Implementation of Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras CVPR2021 CV4Animals Workshop P

44 Jan 06, 2023
Adaptive FNO transformer - official Pytorch implementation

Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers This repository contains PyTorch implementation of the Adaptive Fourier Neu

NVIDIA Research Projects 77 Dec 29, 2022
A library for using chemistry in your applications

Chemistry in python Resources Used The following items are not made by me! Click the words to go to the original source Periodic Tab Json - Used in -

Tech Penguin 28 Dec 17, 2021
Unsupervised Discovery of Object Radiance Fields

Unsupervised Discovery of Object Radiance Fields by Hong-Xing Yu, Leonidas J. Guibas and Jiajun Wu from Stanford University. arXiv link: https://arxiv

Hong-Xing Yu 148 Nov 30, 2022
Code for generating a single image pretraining dataset

Single Image Pretraining of Visual Representations As shown in the paper A critical analysis of self-supervision, or what we can learn from a single i

Yuki M. Asano 12 Dec 19, 2022
FS-Mol: A Few-Shot Learning Dataset of Molecules

FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation

Microsoft 114 Dec 15, 2022
Gym environments used in the paper: "Developmental Reinforcement Learning of Control Policy of a Quadcopter UAV with Thrust Vectoring Rotors"

gym_multirotor Gym to train reinforcement learning agents on UAV platforms Quadrotor Tiltrotor Requirements This package has been tested on Ubuntu 18.

Aditya M. Deshpande 19 Dec 29, 2022