PyDPF
PyDPF is an extensible package for differentiable particle filtering. Designed for researchers and practitioners working with deep sequential Monte Carlo methods.
See the full documentation at: https://python-dpf.readthedocs.io/en/latest/index.html
Check out our getting started tutorial at: https://python-dpf.readthedocs.io/en/latest/tutorial.html
If you use this package in your publication please cite our paper:
@article{brady2025pydpf,
title={PyDPF: A Python Package for Differentiable Particle Filtering},
author={John-Joseph Brady and Benjamin Cox and Yunpeng Li and V\'{i}ctor Elvira},
year={2025},
journal={arXiv preprint arXiv:2510.25693},
url={https://arxiv.org/abs/2510.25693},
}
Metadata
Release files for pydpf 1.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pydpf-1.2.2.tar.gz | 5.8 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pydpf-1.2.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 5.9 MB
Release files / pydpf-1.2.2.tar.gz
| Download URL | pydpf-1.2.2.tar.gz |
|---|---|
| Size | 5.8 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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No |
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twine/7.0.0 CPython/3.14.3
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Release files / pydpf-1.2.2-py3-none-any.whl
| Download URL | pydpf-1.2.2-py3-none-any.whl |
|---|---|
| Size | 78.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.14.3
|