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@@ -27,7 +27,25 @@ Neural A\* is a novel data-driven search-based planner that consists of a traina
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## Citation
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```
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# ICML2021 version (to appear)
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# ICML2021 version
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@InProceedings{pmlr-v139-yonetani21a,
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title = {Path Planning using Neural A* Search},
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author = {Ryo Yonetani and
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Tatsunori Taniai and
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Mohammadamin Barekatain and
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Mai Nishimura and
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Asako Kanezaki},
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booktitle = {Proceedings of the 38th International Conference on Machine Learning},
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pages = {12029--12039},
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year = {2021},
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editor = {Meila, Marina and Zhang, Tong},
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volume = {139},
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series = {Proceedings of Machine Learning Research},
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month = {18--24 Jul},
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publisher = {PMLR},
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pdf = {http://proceedings.mlr.press/v139/yonetani21a/yonetani21a.pdf},
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url = {http://proceedings.mlr.press/v139/yonetani21a.html},
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}
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# arXiv version
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@article{DBLP:journals/corr/abs-2009-07476,
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## References
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- [1] [Lisa Lee*, Emilio Parisotto*, Devendra Singh Chaplot, Eric Xing, Ruslan Salakhutdinov, "Gated Path Planning Networks", ICML, 2018.](https://arxiv.org/abs/1806.06408)
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- [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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- [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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