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11 to 20 of 3,559 Results

ro-crate-metadata.json Oct 20, 2026 - Code and Formalized Proofs for: Faithful Box Embeddings for Linear Temporal EL+ RO-Crate metadata - 2.9 KB - MD5: 599d99b182f1a978e6341e088d8aaaa6
runs.tar.gz Oct 20, 2026 - Code and Formalized Proofs for: Faithful Box Embeddings for Linear Temporal EL+ Gzip Archive - 559.6 KB - MD5: 22c0101f5320ec5f5873731f1629ae60
SHA256SUMS Oct 20, 2026 - Code and Formalized Proofs for: Faithful Box Embeddings for Linear Temporal EL+ Plain Text - 915 B - MD5: 23e924348561992bbb07c6f0832bad8e
Scalar Lur'e system with dead-zone nonlinearity for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated Oct 13, 2026 Frank, Daniel, 2026, "Scalar Lur'e system with dead-zone nonlinearity for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated", https://doi.org/10.18419/DARUS-6521, DaRUS, V1 Overview Input-output data of a scalar discrete-time Lur'e system with a dead-zone nonlinearity. The system is regionally but not globally stable: inside the dead zone it is a stable linear system, outside it is unstable. The dataset has two parts: converging trajectories that stay bounded over the whole horizon, and diverging trajectories that sta...
OneD.zip Oct 13, 2026 - Scalar Lur'e system with dead-zone nonlinearity for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated ZIP Archive - 990.5 KB - MD5: 6a330772ba680c81d40d7ae9ffe379b5
README.md Oct 13, 2026 - Scalar Lur'e system with dead-zone nonlinearity for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated Markdown Text - 4.4 KB - MD5: 7bf6666be20105057cc60a809f8209ea
Duffing oscillator for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated Oct 13, 2026 Frank, Daniel, 2026, "Duffing oscillator for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated", https://doi.org/10.18419/DARUS-6520, DaRUS, V1 Overview Input-output data of a damped, softening Duffing oscillator, it also includes the internal state. The system is regionally but not globally stable: the origin is asymptotically stable, but the saddle points (±1, 0) bound its basin of attraction, and inputs that push the state across that boundary make it diverge. The dataset therefore has...
Duffing.zip Oct 13, 2026 - Duffing oscillator for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated ZIP Archive - 11.3 MB - MD5: 5a9f08be6977cc3d79bd27502406f2e2
README.md Oct 13, 2026 - Duffing oscillator for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated Markdown Text - 4.5 KB - MD5: 661448b8ebe1299dcf20f2ba372d5782
MLIPs Ontology Jul 29, 2026 Hernández, Daniel; Jung, Jong Hyun; Ikeda, Yuji; Ou, Yongliang; Kumar, Pranav; Schächtel, Tom; Liu, Wenchuan; Li, Xin; Zhang, Xi; Xu, Xiang; Zhu, Li-Fang; Körmann, Fritz; Staab, Steffen; Grabowski, Blazej, 2026, "MLIPs Ontology", https://doi.org/10.18419/DARUS-5948, DaRUS, V1 MLIPs Ontology: An Ontology for Machine Learning Interatomic Potentials More information can be found in the README.md.

ro-crate-metadata.json

Oct 20, 2026 - Code and Formalized Proofs for: Faithful Box Embeddings for Linear Temporal EL+

RO-Crate metadata - 2.9 KB -

runs.tar.gz

Oct 20, 2026 - Code and Formalized Proofs for: Faithful Box Embeddings for Linear Temporal EL+

Gzip Archive - 559.6 KB -

SHA256SUMS

Oct 20, 2026 - Code and Formalized Proofs for: Faithful Box Embeddings for Linear Temporal EL+

Plain Text - 915 B -

Scalar Lur'e system with dead-zone nonlinearity for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated

Oct 13, 2026

Frank, Daniel, 2026, "Scalar Lur'e system with dead-zone nonlinearity for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated", https://doi.org/10.18419/DARUS-6521, DaRUS, V1

Overview Input-output data of a scalar discrete-time Lur'e system with a dead-zone nonlinearity. The system is regionally but not globally stable: inside the dead zone it is a stable linear system, outside it is unstable. The dataset has two parts: converging trajectories that stay bounded over the whole horizon, and diverging trajectories that sta...

OneD.zip

Oct 13, 2026 - Scalar Lur'e system with dead-zone nonlinearity for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated

ZIP Archive - 990.5 KB -

README.md

Oct 13, 2026 - Scalar Lur'e system with dead-zone nonlinearity for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated

Markdown Text - 4.4 KB -

Duffing oscillator for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated

Oct 13, 2026

Frank, Daniel, 2026, "Duffing oscillator for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated", https://doi.org/10.18419/DARUS-6520, DaRUS, V1

Overview Input-output data of a damped, softening Duffing oscillator, it also includes the internal state. The system is regionally but not globally stable: the origin is asymptotically stable, but the saddle points (±1, 0) bound its basin of attraction, and inputs that push the state across that boundary make it diverge. The dataset therefore has...

Duffing.zip

Oct 13, 2026 - Duffing oscillator for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated

ZIP Archive - 11.3 MB -

README.md

Oct 13, 2026 - Duffing oscillator for nonlinear system identification - regionally stable, with converging and diverging trajectories - synthetically generated

Markdown Text - 4.5 KB -

MLIPs Ontology

Jul 29, 2026

Hernández, Daniel; Jung, Jong Hyun; Ikeda, Yuji; Ou, Yongliang; Kumar, Pranav; Schächtel, Tom; Liu, Wenchuan; Li, Xin; Zhang, Xi; Xu, Xiang; Zhu, Li-Fang; Körmann, Fritz; Staab, Steffen; Grabowski, Blazej, 2026, "MLIPs Ontology", https://doi.org/10.18419/DARUS-5948, DaRUS, V1

MLIPs Ontology: An Ontology for Machine Learning Interatomic Potentials More information can be found in the README.md.

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