PyTorch implementation of Intrinsic-Extrinsic Preserved Generative Adversarial Network (IEP-GAN) for both intrinsic (i.e., shape) and extrinsic (i.e., pose) information preservation. Extrinsically, a co-occurrence discriminator is used to capture the stru... read more of IEP-GAN: Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer

The Lyrics framework injects logic knowledge into a learner using Semantic Based Regularization read more of Lyrics

Tutorial for the Lyrics framework, which provides a Python library to integrate learning from logic constraints and Deep learning models read more of Lyrics Tutorial

A python 2.7 library for Neural-Symbolic integration read more of KENN-Docker

QSRlib is a library that allows the computation of Qualitative Spatial Relations and Calculi, as well as a development framework for rapid implementation of new QSRs. read more of QSRlib

A tutorial for KENN2 library read more of KENN2 - Relational tutorial

The Relational Neural Machines framework is a generakl neuro-symbolic methodology to inject logic knowledge into a machine learner. read more of Relational Neural Machines

A Java API for meta-constraint reasoning read more of Meta-CSP Framework

A repository with some of the models developed and trained for the AI4Hotels project. read more of AI4Hotels forecasting models

Real electric load and occupancy data used to train the forecast models in the AI4Hotels project read more of AI4Hotels data

A Jupyter Notebook demo to demonstrate the partial content of FZI asset "Process integrated feedback management" which uses the historical multivariant time series data from a simulative robot manipulator to predict data in the future time steps based on ... read more of AI REGIO Supervised Learning for Multivariant Time Series Forecasting

This repository includes a jupyter notebook that presents a complete pipeline for: EDA on image data Data preparation and augmentation Deep learning (CNN) models development for image classification with TensorFlow Models evaluation Model interpret... read more of Quality control on production lines with Computer Vision and TinyML