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481 to 490 of 533 Results

Dataset for: Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system Aug 12, 2022 Linardakis, Leonidas, 2022, "Dataset for: Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system", https://doi.org/10.17617/3.FGFQZG, Edmond, V1 This dataset contains the ICON code, the experiments run scripts, and the experiments time results and the derived scaling values, for the article: "Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system". Note that the ICON code is provided here only for docume...
The clinical drug candidate anle138b binds in a cavity of lipidic α-synuclein fibrils Aug 9, 2022 Antonschmidt, Leif; Dirk Matthes; Rıza Dervişoğlu; Benedikt Frieg; Christian Dienemann; Andrei Leonov; Evgeny Nimerovsky; Vrinda Sant; Sergey Ryazanov; Armin Giese; Gunnar Schröder; Stefan Becker; Bert L. de Groot; Christian Griesinger; Loren B. Andreas, 2022, "The clinical drug candidate anle138b binds in a cavity of lipidic α-synuclein fibrils", https://doi.org/10.17617/3.9C6TEW, Edmond, V1 This dataset includes NMR spectra raw data generated in this study, Negative stain EM micrographs for αSyn fibrils in the presence of anle138b and mass spectrometry data for the synthesis of selectively labelled α-synuclein and 13C- and 15N-labelled anle138b, respectively. Solid-state NMR: 3D (H)CANH experiments on fibrils in the presence of anle13...
Atomistic Grain-Boundary Model of the Solid-State-Electrolyte LATP Aug 9, 2022 Scheurer, Christoph, 2022, "Atomistic Grain-Boundary Model of the Solid-State-Electrolyte LATP", https://doi.org/10.17617/3.KJWDRB, Edmond, V1 This data set contains atomistic model structures related to the publication DOI: 10.1002/aenm.202100707 .
The Superconductivity of Sr2RuO4 Under c-Axis Uniaxial Stress Aug 5, 2022 Jerzembeck, Fabian, 2022, "The Superconductivity of Sr2RuO4 Under c-Axis Uniaxial Stress", https://doi.org/10.17617/3.3O1ZM2, Edmond, V1
MPG Geomagnetic field forecast from 2020 to 2120 Aug 4, 2022 Sanchez, Sabrina, 2022, "MPG Geomagnetic field forecast from 2020 to 2120", https://doi.org/10.17617/3.MZGFPM, Edmond, V1 Geomagnetic field forecast from 2020 to 2120, based on the assimilation of COV-OBS.x1 (Gillet et al, 2015) and Kalmag (Baerenzung et al, 2020) by an ensemble of 3D dynamo simulations. The forecast was issued in the context of the IGRF-13 for geomagnetic field forecast between 2020-2025, and published in Sanchez et al (2020, EPS).
Data - Flexible energy-saving strategies in female temperate-zone bats Aug 3, 2022 Keicher, Lara, 2022, "Data - Flexible energy-saving strategies in female temperate-zone bats", https://doi.org/10.17617/3.T5LUIM, Edmond, V1
Dynamic of speech Jul 30, 2022 Larrouy-Maestri, Pauline, 2022, "Dynamic of speech", https://doi.org/10.17617/3.IZWNZ1, Edmond, V1
Molecular dynamics simulations of α-synuclein protofilament structure models without and with anle138b Jul 27, 2022 Matthes, Dirk, 2022, "Molecular dynamics simulations of α-synuclein protofilament structure models without and with anle138b", https://doi.org/10.17617/3.R4FJQG, Edmond, V1
A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models Jul 27, 2022 Agudelo-España, Diego; Zadaianchuk, Andrii; Wenk, Philipp; Garg, Aditya; Akpo, Joel Bessekon; Grimminger, Felix; Viereck, Julian; Naveau, Maximilien; Righetti, Ludovic ‬; Martius, Georg; Krause, Andreas; Schölkopf, Bernhard; Bauer, Stefan; Wüthrich, Manuel, 2022, "A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models", https://doi.org/10.17617/3.ZT6K7P, Edmond, V1 In the context of model-based reinforcement learning and control, a large number of methods for learning system dynamics have been proposed in recent years. The purpose of these learned models is to synthesize new control policies. An important open question is how robust current dynamics-learning methods are to shifts in the data distribution due...
Data For: Systematic Atomic Structure Datasets for Machine Learning Potentials: Application to Defects in Magnesium Jul 22, 2022 Poul, Marvin, 2022, "Data For: Systematic Atomic Structure Datasets for Machine Learning Potentials: Application to Defects in Magnesium", https://doi.org/10.17617/3.A3MB7Z, Edmond, V1 DFT Training Data for fitting Moment Tensor Potentials. See https://github.com/eisenforschung/magnesium-mtp-training-data for further notes and usage examples.

Dataset for: Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system

Aug 12, 2022

Linardakis, Leonidas, 2022, "Dataset for: Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system", https://doi.org/10.17617/3.FGFQZG, Edmond, V1

This dataset contains the ICON code, the experiments run scripts, and the experiments time results and the derived scaling values, for the article: "Improving scalability of Earth System Models through coarse-grained component concurrency - a case study with the ICON v2.6.5 modelling system". Note that the ICON code is provided here only for docume...

The clinical drug candidate anle138b binds in a cavity of lipidic α-synuclein fibrils

Aug 9, 2022

Antonschmidt, Leif; Dirk Matthes; Rıza Dervişoğlu; Benedikt Frieg; Christian Dienemann; Andrei Leonov; Evgeny Nimerovsky; Vrinda Sant; Sergey Ryazanov; Armin Giese; Gunnar Schröder; Stefan Becker; Bert L. de Groot; Christian Griesinger; Loren B. Andreas, 2022, "The clinical drug candidate anle138b binds in a cavity of lipidic α-synuclein fibrils", https://doi.org/10.17617/3.9C6TEW, Edmond, V1

This dataset includes NMR spectra raw data generated in this study, Negative stain EM micrographs for αSyn fibrils in the presence of anle138b and mass spectrometry data for the synthesis of selectively labelled α-synuclein and 13C- and 15N-labelled anle138b, respectively. Solid-state NMR: 3D (H)CANH experiments on fibrils in the presence of anle13...

Atomistic Grain-Boundary Model of the Solid-State-Electrolyte LATP

Aug 9, 2022

Scheurer, Christoph, 2022, "Atomistic Grain-Boundary Model of the Solid-State-Electrolyte LATP", https://doi.org/10.17617/3.KJWDRB, Edmond, V1

This data set contains atomistic model structures related to the publication DOI: 10.1002/aenm.202100707 .

The Superconductivity of Sr2RuO4 Under c-Axis Uniaxial Stress

Aug 5, 2022

Jerzembeck, Fabian, 2022, "The Superconductivity of Sr2RuO4 Under c-Axis Uniaxial Stress", https://doi.org/10.17617/3.3O1ZM2, Edmond, V1

MPG Geomagnetic field forecast from 2020 to 2120

Aug 4, 2022

Sanchez, Sabrina, 2022, "MPG Geomagnetic field forecast from 2020 to 2120", https://doi.org/10.17617/3.MZGFPM, Edmond, V1

Geomagnetic field forecast from 2020 to 2120, based on the assimilation of COV-OBS.x1 (Gillet et al, 2015) and Kalmag (Baerenzung et al, 2020) by an ensemble of 3D dynamo simulations. The forecast was issued in the context of the IGRF-13 for geomagnetic field forecast between 2020-2025, and published in Sanchez et al (2020, EPS).

Data - Flexible energy-saving strategies in female temperate-zone bats

Aug 3, 2022

Keicher, Lara, 2022, "Data - Flexible energy-saving strategies in female temperate-zone bats", https://doi.org/10.17617/3.T5LUIM, Edmond, V1

Dynamic of speech

Jul 30, 2022

Larrouy-Maestri, Pauline, 2022, "Dynamic of speech", https://doi.org/10.17617/3.IZWNZ1, Edmond, V1

Molecular dynamics simulations of α-synuclein protofilament structure models without and with anle138b

Jul 27, 2022

Matthes, Dirk, 2022, "Molecular dynamics simulations of α-synuclein protofilament structure models without and with anle138b", https://doi.org/10.17617/3.R4FJQG, Edmond, V1

A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models

Jul 27, 2022

Agudelo-España, Diego; Zadaianchuk, Andrii; Wenk, Philipp; Garg, Aditya; Akpo, Joel Bessekon; Grimminger, Felix; Viereck, Julian; Naveau, Maximilien; Righetti, Ludovic ‬; Martius, Georg; Krause, Andreas; Schölkopf, Bernhard; Bauer, Stefan; Wüthrich, Manuel, 2022, "A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models", https://doi.org/10.17617/3.ZT6K7P, Edmond, V1

In the context of model-based reinforcement learning and control, a large number of methods for learning system dynamics have been proposed in recent years. The purpose of these learned models is to synthesize new control policies. An important open question is how robust current dynamics-learning methods are to shifts in the data distribution due...

Data For: Systematic Atomic Structure Datasets for Machine Learning Potentials: Application to Defects in Magnesium

Jul 22, 2022

Poul, Marvin, 2022, "Data For: Systematic Atomic Structure Datasets for Machine Learning Potentials: Application to Defects in Magnesium", https://doi.org/10.17617/3.A3MB7Z, Edmond, V1

DFT Training Data for fitting Moment Tensor Potentials. See https://github.com/eisenforschung/magnesium-mtp-training-data for further notes and usage examples.

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