Java and SHACL code commented in the paper "Towards compliance checking in reified I/O logic via SHACL" submitted to ICAIL 2021

Related tags

Deep LearningshRIOL
Overview

shRIOL

The subfolder shRIOL contains Java files to execute the SHACL files on the OWL ontology.

To compile the Java files: "javac -cp ./src/;./lib/* -d ./class ./src/DetectViolations.java"
To run compiled class files: "java -cp ./class;./lib/* DetectViolations"

By executing the Java files, the following messages are printed on screen. See the paper for more details and explanations.

The model is not GDPR-compliant. The following violations have been detected:
----------------------------------------------------------------------------------------------
Personal Data Processing: http://w3.org/ns/shRIOL#pdpHans
MESSAGE: The personal data processing is not transparent, as required/defined by Article 12 of the GDPR
EXPLANATION: Specifically, these legal authorities judged one or more communications related to pdpHans as follows:
	- courtA does NOT deem the communication c2Hans enough readable.
	- courtB deems the communication c2Hans enough readable.
----------------------------------------------------------------------------------------------
Personal Data Processing: http://w3.org/ns/shRIOL#pdpLuca
MESSAGE: The personal data processing is not lawful, as required by Art.5(1)(a) and defined by Art.6 of the GDPR.
EXPLANATION: The age of the data subject is below the minimal age for consent in his/her Member State. See Art.8(1) of the GDPR.
----------------------------------------------------------------------------------------------
[NeurIPS'20] Self-supervised Co-Training for Video Representation Learning. Tengda Han, Weidi Xie, Andrew Zisserman.

CoCLR: Self-supervised Co-Training for Video Representation Learning This repository contains the implementation of: InfoNCE (MoCo on videos) UberNCE

Tengda Han 271 Jan 02, 2023
Supervised multi-SNE (S-multi-SNE): Multi-view visualisation and classification

S-multi-SNE Supervised multi-SNE (S-multi-SNE): Multi-view visualisation and classification A repository containing the code to reproduce the findings

Theodoulos Rodosthenous 3 Apr 15, 2022
An original implementation of "MetaICL Learning to Learn In Context" by Sewon Min, Mike Lewis, Luke Zettlemoyer and Hannaneh Hajishirzi

MetaICL: Learning to Learn In Context This includes an original implementation of "MetaICL: Learning to Learn In Context" by Sewon Min, Mike Lewis, Lu

Meta Research 141 Jan 07, 2023
Attention-driven Robot Manipulation (ARM) which includes Q-attention

Attention-driven Robotic Manipulation (ARM) This codebase is home to: Q-attention: Enabling Efficient Learning for Vision-based Robotic Manipulation I

Stephen James 84 Dec 29, 2022
Pre-trained NFNets with 99% of the accuracy of the official paper

NFNet Pytorch Implementation This repo contains pretrained NFNet models F0-F6 with high ImageNet accuracy from the paper High-Performance Large-Scale

Benjamin Schmidt 133 Dec 09, 2022
PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

DiscoGAN in PyTorch PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks. * All samples in READM

Taehoon Kim 1k Jan 04, 2023
Reproduction process of AlexNet

PaddlePaddle论文复现杂谈 背景 注:该repo基于PaddlePaddle,对AlexNet进行复现。时间仓促,难免有所疏漏,如果问题或者想法,欢迎随时提issue一块交流。 飞桨论文复现赛地址:https://aistudio.baidu.com/aistudio/competitio

19 Nov 29, 2022
Gapmm2: gapped alignment using minimap2 (align transcripts to genome)

gapmm2: gapped alignment using minimap2 This tool is a wrapper for minimap2 to r

Jon Palmer 2 Jan 27, 2022
Cascading Feature Extraction for Fast Point Cloud Registration (BMVC 2021)

Cascading Feature Extraction for Fast Point Cloud Registration This repository contains the source code for the paper [Arxive link comming soon]. Meth

7 May 26, 2022
PyTea: PyTorch Tensor shape error analyzer

PyTea: PyTorch Tensor Shape Error Analyzer paper project page Requirements node.js = 12.x python = 3.8 z3-solver = 4.8 How to install and use # ins

ROPAS Lab. 240 Jan 02, 2023
neural image generation

pixray Pixray is an image generation system. It combines previous ideas including: Perception Engines which uses image augmentation and iteratively op

dribnet 398 Dec 17, 2022
Sudoku solver - A sudoku solver with python

sudoku_solver A sudoku solver What is Sudoku? Sudoku (Japanese: 数独, romanized: s

Sikai Lu 0 May 22, 2022
PINN Burgers - 1D Burgers equation simulated by PINN

PINN(s): Physics-Informed Neural Network(s) for Burgers equation This is an impl

ShotaDEGUCHI 1 Feb 12, 2022
nnFormer: Interleaved Transformer for Volumetric Segmentation Code for paper "nnFormer: Interleaved Transformer for Volumetric Segmentation "

nnFormer: Interleaved Transformer for Volumetric Segmentation Code for paper "nnFormer: Interleaved Transformer for Volumetric Segmentation ". Please

jsguo 610 Dec 28, 2022
OpenGAN: Open-Set Recognition via Open Data Generation

OpenGAN: Open-Set Recognition via Open Data Generation ICCV 2021 (oral) Real-world machine learning systems need to analyze novel testing data that di

Shu Kong 90 Jan 06, 2023
Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs

Project Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs, https://arxiv.org/pdf/2111.01940.pdf. Authors Truong Son Hy

5 Jun 28, 2022
Face-Recognition-based-Attendance-System - An implementation of Attendance System in python.

Face-Recognition-based-Attendance-System A real time implementation of Attendance System in python. Pre-requisites To understand the implentation of F

Muhammad Zain Ul Haque 1 Dec 31, 2021
A framework for analyzing computer vision models with simulated data

3DB: A framework for analyzing computer vision models with simulated data Paper Quickstart guide Blog post Installation Follow instructions on: https:

3DB 112 Jan 01, 2023
[CoRL 21'] TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo

TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo Lukas Koestler1*    Nan Yang1,2*,†    Niclas Zeller2,3    Daniel Cremers1

TUM Computer Vision Group 744 Jan 04, 2023
PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners for self-supervised ViT.

MAE for Self-supervised ViT Introduction This is an unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners for self-sup

36 Oct 30, 2022