particle2seq | Sequence modelling applied to event collisions

by Justin-Tan Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | particle2seq Summary

particle2seq is a Python library. particle2seq has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However particle2seq build file is not available. You can download it from GitHub.

A sequence modelling approach to event classification in particle physics, which naturally supports events with variable numbers of particles in the decay chain. This is designed to be used in conjunction with traditional approaches to background suppression based on high-level engineered features. workshop.pdf can be consulted for further details.

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Support

particle2seq has a low active ecosystem.

It has 4 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

particle2seq has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of particle2seq is current.

Quality

particle2seq has no bugs reported.

Security

particle2seq has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

particle2seq is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

particle2seq releases are not available. You will need to build from source code and install.

particle2seq has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed particle2seq and discovered the below as its top functions. This is intended to give you an instant insight into particle2seq implemented functionality, and help decide if they suit your requirements.

Train the network
Plot distributions for a given model
Run diagnostics
Runs diagnostics
Load features from file
Binar network
Soft attention
Calculate the last relevant output
Compute the length of a sequence
Evaluate the model
Binder

Get all kandi verified functions for this library.

particle2seq Key Features

No Key Features are available at this moment for particle2seq.

particle2seq Examples and Code Snippets

No Code Snippets are available at this moment for particle2seq.

Community Discussions

No Community Discussions are available at this moment for particle2seq.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install particle2seq

You can download it from GitHub.
You can use particle2seq like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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