Bounded Levenberg-Marquardt algorithm for batch optimization
Project description
LMtorch
Bounded Levenberg-Marquardt algorithm for batch optimization Acknowledgments
This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 813120.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
LMtorch-0.0.0.tar.gz
(4.3 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file LMtorch-0.0.0.tar.gz.
File metadata
- Download URL: LMtorch-0.0.0.tar.gz
- Upload date:
- Size: 4.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
7e44e2975026e90e8134a368f54e07d7291a992236ad6f51ed4182d386361709
|
|
| MD5 |
f80fd759ab467ae6f803479f1a2ce06c
|
|
| BLAKE2b-256 |
48d4380f68dc4cf31247d8a18cd0fbfe4f2d27eef232c0a8a6c1ceff348a123a
|
File details
Details for the file LMtorch-0.0.0-py3-none-any.whl.
File metadata
- Download URL: LMtorch-0.0.0-py3-none-any.whl
- Upload date:
- Size: 3.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
7a6598551c401c5284422825fa52ae22dbcb160205f0f7b5688a9b90fdb549ee
|
|
| MD5 |
66b062e193a4014bfb514ec9ed150776
|
|
| BLAKE2b-256 |
1964c2c780315a97b19afb001584f461faa91cb95285ac543c369029196059d6
|
