This is the PyTorch implementation of Particle Filter Recurrent Neural Networks (PF-RNNs).
Xiao Ma, Peter Karkus, David Hsu, Wee Sun Lee: Particle Filter Recurrent Neural Networks. AAAI Conference on Artificial Intelligence (AAAI), 2020.
Above is the network structures for PF-LSTM and PF-GRU. In PF-RNNs, we maintain a set of latent particles and update them using particle filter algorithm. In our implementation, PF-LSTM and PF-GRU update particles in a parallel manner which benefit from the GPU acceleration.
pip install -r requirements.txt
The training parameters are specified in configs/train.conf. To run the robot localization experiment, use
python main.py -c ./configs/train.conf
If you find this work useful, please consider citing us
@article{ma2019particle,
title={Particle Filter Recurrent Neural Networks},
author={Ma, Xiao and Karkus, Peter and Hsu, David and Lee, Wee Sun},
journal={arXiv preprint arXiv:1905.12885},
year={2019}
}