recurrent-memory | neural networks learn sequential vs. persistent solutions

by eminorhan Python Version: Current License: LGPL-3.0

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kandi X-RAY | recurrent-memory Summary

recurrent-memory is a Python library. recurrent-memory has no bugs, it has no vulnerabilities, it has a Weak Copyleft License and it has low support. However recurrent-memory build file is not available. You can download it from GitHub.

This repository contains the code for reproducing the results reported in the following paper:. Orhan AE, Ma WJ (2019) A diverse range of factors affect the nature of neural representations underlying short-term memory. Nature Neuroscience, 22, 275–283. The code is written in Theano (0.8.2) + Lasagne (0.2.dev1). The code was originally run on a local computer cluster. If you are interested in running the following experiments on a cluster, I have some simple shell scripts that can facilitate this. Please contact me about this or about any other questions or concerns. You can find my contact information on my web page.

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Support

recurrent-memory has a low active ecosystem.

It has 12 star(s) with 9 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

recurrent-memory has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of recurrent-memory is current.

Quality

recurrent-memory has no bugs reported.

Security

recurrent-memory has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

recurrent-memory is licensed under the LGPL-3.0 License. This license is Weak Copyleft.

Weak Copyleft licenses have some restrictions, but you can use them in commercial projects.

Reuse

recurrent-memory releases are not available. You will need to build from source code and install.

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

Build a model
Generate a GRU
Initializes recurrent layer
Initialize recurrent layer

Get all kandi verified functions for this library.

recurrent-memory Key Features

No Key Features are available at this moment for recurrent-memory.

recurrent-memory Examples and Code Snippets

No Code Snippets are available at this moment for recurrent-memory.

Community Discussions

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

Vulnerabilities

No vulnerabilities reported

Install recurrent-memory

You can download it from GitHub.
You can use recurrent-memory 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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