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Subject: Computer and Information Science Publication Year: 2022 License: CC BY 4.0

1 to 10 of 51 Results

PDEBench Datasets Feb 13, 2024 - SciML PDE Benchmark Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Datasets", https://doi.org/10.18419/darus-2986, DaRUS, V8 This dataset contains benchmark data, generated with numerical simulation based on different PDEs, namely 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D shallow water equation. This...
PDEBench Pretrained Models Nov 30, 2023 - SciML PDE Benchmark Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Pretrained Models", https://doi.org/10.18419/darus-2987, DaRUS, V2 This dataset contains the pretrained baseline models, namely FNO, U-Net, and PINN. These models are trained on different PDEs, such as 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D...
Replication Data for: A mass-conserving sparse grid combination technique with biorthogonal hierarchical basis functions for kinetic simulations Apr 20, 2023 - Publications Pollinger, Theresa, 2022, "Replication Data for: A mass-conserving sparse grid combination technique with biorthogonal hierarchical basis functions for kinetic simulations", https://doi.org/10.18419/darus-2790, DaRUS, V2 Replication data for advection, Landau damping, and two-stream instability experiments with mass-conserving basis functions (vs hat functions) in the combination technique. The simulations are based on the DisCoTec and SeLaLib codes. If you want to re-generate the numerical data,...
Quality Assurance Forms for Grey Literature Studies Supporting Cross-chain Smart Contract Invocations Nov 30, 2022 - Architectures and Middleware @IAAS Falazi, Ghareeb; Breitenbücher, Uwe; Leymann, Frank; Schulte, Stefan, 2022, "Quality Assurance Forms for Grey Literature Studies Supporting Cross-chain Smart Contract Invocations", https://doi.org/10.18419/darus-3283, DaRUS, V1 Forms that estimate the quality of candidate grey literature studies to be included in the multi-vocal literature review entitled, "Cross-Chain Smart Contract Invocations: A Systematic Multi-Vocal Literature Review".
Selection, Data Extraction, and Data Synthesis for Cross-chain Smart Contract Invocation Approaches Nov 30, 2022 - Architectures and Middleware @IAAS Falazi, Ghareeb; Breitenbücher, Uwe; Leymann, Frank; Schulte, Stefan, 2022, "Selection, Data Extraction, and Data Synthesis for Cross-chain Smart Contract Invocation Approaches", https://doi.org/10.18419/darus-3282, DaRUS, V1 This document contains information about: All the studies that were initially accepted for inclusion in the Multi-vocal Systematic Literature review. The studies that were rejected in the second phase and the reasons for their rejection. Filled out data extraction form for the fi...
Qualitative Visual Analysis of Cross-chain Smart Contract Invocation Approaches Nov 30, 2022 - Architectures and Middleware @IAAS Falazi, Ghareeb; Breitenbücher, Uwe; Leymann, Frank; Schulte, Stefan, 2022, "Qualitative Visual Analysis of Cross-chain Smart Contract Invocation Approaches", https://doi.org/10.18419/darus-3281, DaRUS, V1 This document demonstrates the visual qualitative analysis performed over the approaches systematically selected for inclusion in the study entitled, "Cross-Chain Smart Contract Invocations: A Systematic Multi-Vocal Literature Review".
Cross-chain Smart Contract Invocations - a Multi-vocal Literature Review Protocol Nov 30, 2022 - Architectures and Middleware @IAAS Falazi, Ghareeb; Breitenbücher, Uwe; Leymann, Frank; Schulte, Stefan, 2022, "Cross-chain Smart Contract Invocations - a Multi-vocal Literature Review Protocol", https://doi.org/10.18419/darus-3280, DaRUS, V1 This document introduces the protocol that describes how a Multivocal Literature Review (MLR) regarding Cross-chain Smart Contract Invocation (CCSCI) was planned to be conducted. The main purpose of having this protocol is to avoid bias when selecting primary sources and processi...
Website Screenshot to Eye-Gaze Nov 17, 2022 - Udeco-EyeGaze Aspandi Latif, Decky, 2022, "Website Screenshot to Eye-Gaze", https://doi.org/10.18419/darus-3251, DaRUS, V1 This dataset contains unified datasets that consist of two pre-processed datasets of Gaze-Mining and Contrastive-Website to allow for the development of Machine Learning based model Eye-Gaze location predictions using Website Screenshot Input.
Constrained Dynamic Mode Decomposition - Supplemental Material Nov 9, 2022 - Visualisierungsinstitut der Universität Stuttgart Krake, Tim; Klötzl, Daniel; Eberhardt, Bernhard; Weiskopf, Daniel, 2022, "Constrained Dynamic Mode Decomposition - Supplemental Material", https://doi.org/10.18419/darus-3107, DaRUS, V1 In this supplemental material, we provide additional application results of constrained Dynamic Mode Decomposition and a parameter study for the delay parameter d that complement the evaluation in the main document: The paper on Constrained Dynamic Mode Decomposition published wi...
Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network Nov 2, 2022 - PN 5-6 Praditia, Timothy; Karlbauer, Matthias; Otte, Sebastian; Oladyshkin, Sergey; Butz, Martin V.; Nowak, Wolfgang, 2022, "Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network", https://doi.org/10.18419/darus-3249, DaRUS, V1 This dataset contains diffusion-sorption data, generated with numerical simulation based on three different sorption isotherms, namely the linear, Freundlich, and Langmuir isotherms. This dataset is used to train, validate, and test all the deep learning models that are used in t...

PDEBench Datasets

Feb 13, 2024 - SciML PDE Benchmark

Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Datasets", https://doi.org/10.18419/darus-2986, DaRUS, V8

This dataset contains benchmark data, generated with numerical simulation based on different PDEs, namely 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D shallow water equation. This...

PDEBench Pretrained Models

Nov 30, 2023 - SciML PDE Benchmark

Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Pretrained Models", https://doi.org/10.18419/darus-2987, DaRUS, V2

This dataset contains the pretrained baseline models, namely FNO, U-Net, and PINN. These models are trained on different PDEs, such as 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D...

Replication Data for: A mass-conserving sparse grid combination technique with biorthogonal hierarchical basis functions for kinetic simulations

Apr 20, 2023 - Publications

Pollinger, Theresa, 2022, "Replication Data for: A mass-conserving sparse grid combination technique with biorthogonal hierarchical basis functions for kinetic simulations", https://doi.org/10.18419/darus-2790, DaRUS, V2

Replication data for advection, Landau damping, and two-stream instability experiments with mass-conserving basis functions (vs hat functions) in the combination technique. The simulations are based on the DisCoTec and SeLaLib codes. If you want to re-generate the numerical data,...

Quality Assurance Forms for Grey Literature Studies Supporting Cross-chain Smart Contract Invocations

Nov 30, 2022 - Architectures and Middleware @IAAS

Falazi, Ghareeb; Breitenbücher, Uwe; Leymann, Frank; Schulte, Stefan, 2022, "Quality Assurance Forms for Grey Literature Studies Supporting Cross-chain Smart Contract Invocations", https://doi.org/10.18419/darus-3283, DaRUS, V1

Forms that estimate the quality of candidate grey literature studies to be included in the multi-vocal literature review entitled, "Cross-Chain Smart Contract Invocations: A Systematic Multi-Vocal Literature Review".

Selection, Data Extraction, and Data Synthesis for Cross-chain Smart Contract Invocation Approaches

Nov 30, 2022 - Architectures and Middleware @IAAS

Falazi, Ghareeb; Breitenbücher, Uwe; Leymann, Frank; Schulte, Stefan, 2022, "Selection, Data Extraction, and Data Synthesis for Cross-chain Smart Contract Invocation Approaches", https://doi.org/10.18419/darus-3282, DaRUS, V1

This document contains information about: All the studies that were initially accepted for inclusion in the Multi-vocal Systematic Literature review. The studies that were rejected in the second phase and the reasons for their rejection. Filled out data extraction form for the fi...

Qualitative Visual Analysis of Cross-chain Smart Contract Invocation Approaches

Nov 30, 2022 - Architectures and Middleware @IAAS

Falazi, Ghareeb; Breitenbücher, Uwe; Leymann, Frank; Schulte, Stefan, 2022, "Qualitative Visual Analysis of Cross-chain Smart Contract Invocation Approaches", https://doi.org/10.18419/darus-3281, DaRUS, V1

This document demonstrates the visual qualitative analysis performed over the approaches systematically selected for inclusion in the study entitled, "Cross-Chain Smart Contract Invocations: A Systematic Multi-Vocal Literature Review".

Cross-chain Smart Contract Invocations - a Multi-vocal Literature Review Protocol

Nov 30, 2022 - Architectures and Middleware @IAAS

Falazi, Ghareeb; Breitenbücher, Uwe; Leymann, Frank; Schulte, Stefan, 2022, "Cross-chain Smart Contract Invocations - a Multi-vocal Literature Review Protocol", https://doi.org/10.18419/darus-3280, DaRUS, V1

This document introduces the protocol that describes how a Multivocal Literature Review (MLR) regarding Cross-chain Smart Contract Invocation (CCSCI) was planned to be conducted. The main purpose of having this protocol is to avoid bias when selecting primary sources and processi...

Website Screenshot to Eye-Gaze

Nov 17, 2022 - Udeco-EyeGaze

Aspandi Latif, Decky, 2022, "Website Screenshot to Eye-Gaze", https://doi.org/10.18419/darus-3251, DaRUS, V1

This dataset contains unified datasets that consist of two pre-processed datasets of Gaze-Mining and Contrastive-Website to allow for the development of Machine Learning based model Eye-Gaze location predictions using Website Screenshot Input.

Constrained Dynamic Mode Decomposition - Supplemental Material

Nov 9, 2022 - Visualisierungsinstitut der Universität Stuttgart

Krake, Tim; Klötzl, Daniel; Eberhardt, Bernhard; Weiskopf, Daniel, 2022, "Constrained Dynamic Mode Decomposition - Supplemental Material", https://doi.org/10.18419/darus-3107, DaRUS, V1

In this supplemental material, we provide additional application results of constrained Dynamic Mode Decomposition and a parameter study for the delay parameter d that complement the evaluation in the main document: The paper on Constrained Dynamic Mode Decomposition published wi...

Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network

Nov 2, 2022 - PN 5-6

Praditia, Timothy; Karlbauer, Matthias; Otte, Sebastian; Oladyshkin, Sergey; Butz, Martin V.; Nowak, Wolfgang, 2022, "Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network", https://doi.org/10.18419/darus-3249, DaRUS, V1

This dataset contains diffusion-sorption data, generated with numerical simulation based on three different sorption isotherms, namely the linear, Freundlich, and Langmuir isotherms. This dataset is used to train, validate, and test all the deep learning models that are used in t...

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