- Info:
See <https://arxiv.org/abs/1406.6651> for theoretical background
- Author:
ZeD@UChicago <zed.uchicago.edu>
- Description:
Implementation of the Deep Granger net inference algorithm, described in https://arxiv.org/abs/1406.6651, for learning spatio-temporal stochastic processes (point processes). cynet learns a network of generative local models, without assuming any specific model structure.
1 maintainer
Metadata
1 maintainer
Release files for Znet 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| Znet-0.0.1.tar.gz | 12.6 kB | Details |
Release files / Znet-0.0.1.tar.gz
| Download URL | Znet-0.0.1.tar.gz |
|---|---|
| Size | 12.6 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
aa9991531c8bff709b6a5f7a8e09ef00576c777901441e476f7d9cd3dde5a6a2
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f9c617e156f70d1f6326af6699519086a7daa2a25bc57141904d0d7bce3af929
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| Uploaded via |
Python-urllib/3.6
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