PyTorch implementation of the semi-markov dBCQ RL model
Project description
SMDP-BCQ
This repository contains an installable version of the SMDP-BCQ model.
Installation
The model has been tested using Python 3.9 and PyTorch 1.9. To install using Pip:
$ python3 -m pip install pytorch_smdbcq
Demo
$ python3 -m smdbcq --demo
See also
Our application of this model to warfarin dosing (under review) and experiments validating its estimation (CHIL 2022).
Project details
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
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 pytorch-smdbcq-0.0.1.tar.gz.
File metadata
- Download URL: pytorch-smdbcq-0.0.1.tar.gz
- Upload date:
- Size: 8.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
11706d2ab4652281a32a3e858e5fc67575eb768873b432447b6929c3fb1d480b
|
|
| MD5 |
84549edb1ab4b8fc9c485f7d09228dcc
|
|
| BLAKE2b-256 |
4f35bf53e7567bf838c8d79f44b8339835e997acb34eb97774c5ba69013b63cb
|
File details
Details for the file pytorch_smdbcq-0.0.1-py3-none-any.whl.
File metadata
- Download URL: pytorch_smdbcq-0.0.1-py3-none-any.whl
- Upload date:
- Size: 11.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1fef6acd9d61714cc245e1cc0ccc35aa0e7663216fb1746b619f56827fe4b9b0
|
|
| MD5 |
2bbd2744df31c603d6d977dbab53d652
|
|
| BLAKE2b-256 |
0b6efc54ebdb887b28bcc31576e14764971e884cf9128127e500ebeeaf59c703
|