ML4EFT is a general open-source framework for the integration of unbinned multivariate observables into global fits of particle physics data. It makes use of machine learning regression and classification techniques to parameterise high-dimensional likelihood ratios, and can be seamlessly integrated into global analyses of, for example, the Standard Model Effective Field Theory and Parton Distribution Functions.
1 maintainer
Metadata
1 maintainer
Release files for ml4eft 0.0.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ml4eft-0.0.5.tar.gz | 30.6 kB | Details |
Release files / ml4eft-0.0.5.tar.gz
| Download URL | ml4eft-0.0.5.tar.gz |
|---|---|
| Size | 30.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
6048b34221c4217796f58058a3763852fa016b6264b696f0f78a1d44df645e8d
|
|
BLAKE2b-256 checksum How to use checksums |
95e0c6c25bd4c4fc149e346d04dd191ed3b3cba7efcf5d9d9c1b6eaf8a364402
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.8.2 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.7.9
|
