Data · dataset · 2023
Pre-trained and fine-tuned ANI models for: Transfer learning for chemically accurate interatomic neural network potentials
Listed in DaRUS
Pre-trained and fine-tuned ANI models using the Gaussian Moments Neural Network (GM-NN) approach.
Description
Code for GM-NN implemented within the Tensorflow framework, including the respective documentation and tutorials, can be found on GitLab. The data represents TensorFlow v2 checkpoints and stores the metadata for the checkpoint and parameters for the model.
Checkpoints can be read by the source code provided on GitLab. A detailed description for reproducing the results and employing pre-trained and fine-tuned models during a simulation is provided in the GM-NN Documentation.
Links
Where it is published
- Dataverse dataset page darus.uni-stuttgart.de/dataset.xhtml?persistentId=doi%3A10.18419%2FDARUS-3299 ↗
landing page · from darus uni stuttgart de
- DOI doi.org/10.18419/darus-3299 ↗
DOI / persistent id · from darus uni stuttgart de
Catalogue records · 1
- Dataverse API darus.uni-stuttgart.de/api/datasets/:persistentId/?persistentId=doi%3A10.18419%2FDARU… ↗
metadata API · from darus uni stuttgart de
Topics
- Stated by source
- Chemistry · Computer and Information Science · Physics
- From keywords
- Chemistry · Computer Science & AI · Energy · Life Sciences · Physics
- Inferred from text
- Machine learning 73% · Simulation 75%
Provenance · 1 source records, 16 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DaRUS | doi:10.18419/DARUS-3299 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4611 | enrichment · darus uni stuttgart de | taxonomy-embedding@1.1.0 | title+keywords+description (73%) |
| concepts[field].dataverse_subject:chemistry | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].dataverse_subject:computer-and-information-science | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].dataverse_subject:physics | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:chemistry | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:energy | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:physics | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[method].local:method:simulation | enrichment · darus uni stuttgart de | keyword-concept-rules@1.0.0 | title+description (75%) |
| created_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| description | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /description |
| publication_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| title | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /name |
| updated_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| version_label | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 |