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1 to 9 of 9 Results
Feb 21, 2024 - Analytic Computing
Asma, Zubaria; Hernández, Daniel; Galárraga, Luis; Flouris, Giorgos; Fundulaki, Irini; Hose, Katja, 2024, "Code and benchmark for NPCS, a Native Provenance Computation for SPARQL", https://doi.org/10.18419/darus-3973, DaRUS, V1
Code for the implementation and benchmark of NPCS, a Native Provenance Computation for SPARQL. The code in this dataset includes the implementation of the NPCS system, which is a middleware for SPARQL endpoints that rewrites queries to queries that annotate answers with provenanc...
Feb 16, 2024 - Analytic Computing
Seifer, Philipp; Hernández, Daniel; Lämmel, Ralf; Staab, Steffen, 2024, "Code for From Shapes to Shapes", https://doi.org/10.18419/darus-3977, DaRUS, V1
This dataset contains the implementation code for an algorithm to infer SHACL shapes that the graph returned by an SPARQL CONSTRUCT query must satisfy if the input satisfies a given set of SHACL shapes. This dataset also includes an evaluation for the algorithm. The algorithm imp...
Dec 11, 2023 - ABxM Framework for Agent-based Modeling and Simulation
Schwinn, Tobias; Groenewolt, Abel; Nguyen, Long; Siriwardena, Lasath; Alvarez, Martín; Reiner, Alexander; Zorn, Max Benjamin; Menges, Achim, 2023, "ABxM.PlateStructures: Agent-based Architectural Design of Plate Structures", https://doi.org/10.18419/darus-3438, DaRUS, V3
ABxM.PlateStructures is an add-on to ABxM.Core for agent-based design and development of plate structures, such as segmented timber shells. The add-on contains various agent system constructs and utilities for plate structure design and is intended to be used within Rhino/Grassho...
Jul 25, 2023 - PN 6-4
Schäfer, Noel; Tilli, Pascal; Munz-Körner, Tanja; Künzel, Sebastian; Vidyapu, Sandeep; Vu, Ngoc Thang; Weiskopf, Daniel, 2023, "Visual Analysis System for Scene-Graph-Based Visual Question Answering", https://doi.org/10.18419/darus-3589, DaRUS, V1
Source code of our visual analysis system to explore scene-graph-based visual question answering. This approach is built on top of the state-of-the-art GraphVQA framework which was trained on the GQA dataset. Instructions on how to use our system can be found in the README.
Jun 16, 2023 - Institute for Structural Mechanics
Tkachuk, Anton; Krake, Tim; Gade, Jan; von Scheven, Malte, 2023, "Matlab Implementation of Efficient Computation of Redundancy Matrices", https://doi.org/10.18419/darus-3347, DaRUS, V1
This is a Demo for the manuscript 'Efficient Computation of Redundancy Matrices for Moderately Redundant Truss and Frames Structures' that demonstrates the speedup of the proposed algorithms. The computation is done in single-precision. Please open and run the main file. Further...
Oct 12, 2022 - Institute for Structural Mechanics
Krake, Tim; von Scheven, Malte, 2022, "Matlab Implementation of Efficient Updates of Redundancy Matrices", https://doi.org/10.18419/darus-2870, DaRUS, V1
This is a Demo for the manuscript 'Efficient Update of Redundancy Matrices for Truss and Frame Structures' that demonstrates the speedup and accuracy of the proposed update formulas. The computation is done in single-precision. Please open and run the main file. Further informati...
Jan 26, 2022 - PN 6-4
Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2022, "NMTVis - Extended Neural Machine Translation Visualization System", https://doi.org/10.18419/darus-2124, DaRUS, V1
NMTVis is a web-based visual analytics system to analyze, understand, and correct translations generated with neural machine translation. First, a document can be translated using a neural machine translation model (we support an LSTM-based and the Transformer architecture). Afte...
May 26, 2021 - PN 6-4
Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2021, "NMTVis - Neural Machine Translation Visualization System", https://doi.org/10.18419/darus-1849, DaRUS, V1
NMTVis is a web-based visual analytics system to analyze, understand, and correct translations generated with neural machine translation. First, a document can be translated using a neural machine translation model (we support an LSTM-based and the Transformer architecture). Afte...
Nov 2, 2020 - PN 6-4
Munz, Tanja; Schäfer, Noel; Blascheck, Tanja; Kurzhals, Kuno; Zhang, Eugene; Weiskopf, Daniel, 2020, "Supplemental Material for Comparative Visual Gaze Analysis for Virtual Board Games", https://doi.org/10.18419/darus-1130, DaRUS, V1
Supplemental material for "Comparative Visual Gaze Analysis for Virtual Board Games". Contains the source code, an executable file, an example data set, a video for demonstration of the analysis system and additional information about Go. The analysis system supports eye tracking...
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