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Ryo Yonetani authored Jul 14, 2021
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Expand Up @@ -27,7 +27,25 @@ Neural A\* is a novel data-driven search-based planner that consists of a traina
## Citation

```
# ICML2021 version (to appear)
# ICML2021 version
@InProceedings{pmlr-v139-yonetani21a,
title = {Path Planning using Neural A* Search},
author = {Ryo Yonetani and
Tatsunori Taniai and
Mohammadamin Barekatain and
Mai Nishimura and
Asako Kanezaki},
booktitle = {Proceedings of the 38th International Conference on Machine Learning},
pages = {12029--12039},
year = {2021},
editor = {Meila, Marina and Zhang, Tong},
volume = {139},
series = {Proceedings of Machine Learning Research},
month = {18--24 Jul},
publisher = {PMLR},
pdf = {http://proceedings.mlr.press/v139/yonetani21a/yonetani21a.pdf},
url = {http://proceedings.mlr.press/v139/yonetani21a.html},
}
# arXiv version
@article{DBLP:journals/corr/abs-2009-07476,
Expand All @@ -54,4 +72,4 @@ This repository includes some code from [RLAgent/gated-path-planning-networks](h

## References
- [1] [Lisa Lee*, Emilio Parisotto*, Devendra Singh Chaplot, Eric Xing, Ruslan Salakhutdinov, "Gated Path Planning Networks", ICML, 2018.](https://arxiv.org/abs/1806.06408)
- [2] [Marin Vlastelica Pogančić, Anselm Paulus, Vit Musil, Georg Martius, Michal Rolinek, "Differentiation of Blackbox Combinatorial Solvers", ICLR, 2020.](https://arxiv.org/abs/1912.02175)
- [2] [Marin Vlastelica Pogančić, Anselm Paulus, Vit Musil, Georg Martius, Michal Rolinek, "Differentiation of Blackbox Combinatorial Solvers", ICLR, 2020.](https://arxiv.org/abs/1912.02175)

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