• Corpus ID: 237266469

ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results

@article{Miolane2021ICLR2C,
  title={ICLR 2021 Challenge for Computational Geometry \& Topology: Design and Results},
  author={Nina Miolane and Matteo Caorsi and Umberto Lupo and Marius Guerard and Nicolas Guigui and Johan Mathe and Yann Cabanes and Wojciech Reise and T. Davies and Ant{\'o}nio Leit{\~a}o and Somesh Mohapatra and Saiteja Utpala and S. Shailja and Guoxi Liu and Federico Iuricich and Andrei Manolache and Mihaela Nistor and Matei Bejan and Armand Mihai Nicolicioiu and Bogdan-Alexandru Luchian and Mihai-Sorin Stupariu and Florent Michel and Khanh Dao Duc and Bilal Abdulrahman and Maxim Beketov and Elodie Maignant and Zhiyuan Liu and Marek vCern'y and Martin Bauw and Santiago Velasco-Forero and Jes{\'u}s Angulo and Yanan Long},
  journal={ArXiv},
  year={2021},
  volume={abs/2108.09810}
}
This paper presents the computational challenge on differential geometry and topology that happened within the ICLR 2021 workshop “Geometric and Topological Representation Learning”. The competition asked participants to provide creative contributions to the fields of computational geometry and topology through the open-source repositories Geomstats and Giotto-TDA. The challenge at- 

ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results

This paper presents the computational challenge on differential geometry and topology that was hosted within the ICLR 2022 workshop “Geometric and Topological Representation Learning”. The

Near out-of-distribution detection for low-resolution radar micro-Doppler signatures

An OOD use case for radar targets detection extensible to other kinds of sensors and detection scenarios is put forward, and a comparison of deep and non-deep OOD methods on simulated low-resolution pulse radar micro-Doppler signatures is proposed.

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