-
Datasets: 100 Heat Pumps + Real Permeability Fields, Simulation - Raw, 4 + 1 ...
This data set serves as training and testing data for modelling the temperature field emanating from open loop groundwater heat pumps (100, randomly placed). It is simulated... -
Datasets: 100 Heat Pumps + Synthetic Permeability Fields, Simulation - Raw, 1...
This data set serves as training and testing data for modelling the temperature field emanating from open loop groundwater heat pumps (100, randomly placed). It is simulated... -
Replication Data for: Improving Data-based Trajectory Generation by Quadratic...
Dataset containing 36000 trajectories generated by an Optimal Control Problem (OCP) for a mobile manipulator with 10 degrees of freedom. The OCP is solved for an initial joint... -
Code for Improving Video Caption Accuracy with LLMs
As part of the IKILeUS project at the University of Stuttgart, research was conducted to explore how Large Language Models (LLMs) can enhance the accuracy and contextual... -
Code for EchoTables (IKILeUS)
EchoTables is an innovative accessibility tool developed as part of the IKILeUS project at the University of Stuttgart. It is designed to improve the usability of tabular data... -
Damped pendulum for nonlinear system identification - inputs are sampled from...
Overview <p>This dataset contains input-output data of a damped nonlinear pendulum that is actuated at the mounting point. The data was generated with... -
Code for statesim - a python package to simulate dynamical systems from ordin...
Python package for simulating ordinary differential equations in state space form. See README.md for details. -
Coupled mass-spring-damper system for nonlinear system identification - actua...
Overview <p>This dataset contains input-output data of a coupled mass-spring-damper system with a nonlinear force profile. The data was generated with... -
Replication Data for: GPRat: Gaussian Process Regression with Asynchronous Tasks
This repository complements the identically titled paper submitted to WAMTA 2025 and allows to reproduce the published results. For a more description please consider the... -
OncoTUM models
OncoTUM models <p> This repository hosts pretrained neural network models for <a href="https://github.com/masud-src/OncoTUM" target="_blank">OncoTUM</a>,... -
Models and Prepared Datasets for 3D-CNN - First Stage
Models trained with Heat Plume Prediction 3D and datasets prepared with Heat Plume Prediction 3D into reasonable format, normalization used to train these models. Based on raw... -
Datasets: First Stage 3D Simulation - Raw, 100 and 1000 Data Points
These data sets serve as training data for modelling the temperature field emanating from a groundwater heat pump. They are simulated with Pflotran and saved in h5 format. They... -
Raw Data for Modeling Heat Plumes of Heat Pumps with varying Flow Directions
Raw datasets for modeling orientational variation in heat plume prediction in groundwater. Used with 1HP NN equivariance. File name explanation: 4d The dataset encompasses... -
Models and Prepared Datasets for Iterative Modeling of Two Heat Pumps
Prepared datasets and models for iterative modeling of heat plumes in groundwater. Models were trained with Iterative modeling. File explanation: 1HP.zip This zip file... -
eSPARQL Implementation
This project contains the code of an implementation of the eSPARQL language, which extends SPARQL-star with a `FROM BELIEF` that allows an easy formulation of epistemic queries.... -
Code for Ultrahyperbolic Knowledge Graph Embeddings
This is a Pytorch implementation of the paper Ultrahyperbolic Knowledge Graph Embeddings published in KDD 2022. This code is used to reproduce the experiments of the method... -
ABxM.Core: The Core Libraries of the ABxM Framework
The ABxM.Core consists of the agent core library ABxM.Core and an interoperability library for Rhino 7 and later versions. ABxM.Core implements the functionality specific to... -
Trained Models on Real Permeability Fields, 4+1 Data Points
Models are trained with Heat Plume Prediction on 4 data points (dp). Steps 1 and 3 of LGCNN (Local Global Convolutional Neural Network) are separate, step 2 is a numerical... -
Trained Vanilla Models on Synthetic Permeability Fields, 101 Data Points
Models are trained with [git: DDUNet] on 101 data points (dp). Both, vanilla UNet and DDU-Net, can be applied directly end-to-end. For inference follow the guidelines of Heat... -
Trained Models on Synthetic Permeability Fields, 3+1 Data Points
Models are trained with Heat Plume Prediction. Steps 1 and 3 of LGCNN (Local Global Convolutional Neural Network) are separate, step 2 is a numerical solver that does not...
