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

Publikation: Konferencebidrag › Paper › Forskning

Standard

ICLR 2022 Challenge for Computational Geometry & Topology : Design and Results. / Myers, Adele ; Sanborn, Sophia ; Donnat, Claire Donnat; Sommer, Stefan Horst.

2022. Paper præsenteret ved ICLR 2022 Workshop on Geometrical and Topological Representation Learnings - ICLR 2022
, Virtual.

Publikation: Konferencebidrag › Paper › Forskning

Harvard

Myers, A, Sanborn, S, Donnat, CD & Sommer, SH 2022, 'ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results', Paper fremlagt ved ICLR 2022 Workshop on Geometrical and Topological Representation Learnings - ICLR 2022
, Virtual, 29/04/2022 - 29/04/2022.

APA

Myers, A., Sanborn, S., Donnat, C. D., & Sommer, S. H. (2022). ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. Paper præsenteret ved ICLR 2022 Workshop on Geometrical and Topological Representation Learnings - ICLR 2022
, Virtual.

Vancouver

Myers A, Sanborn S, Donnat CD, Sommer SH. ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. 2022. Paper præsenteret ved ICLR 2022 Workshop on Geometrical and Topological Representation Learnings - ICLR 2022
, Virtual.

Author

Myers, Adele ; Sanborn, Sophia ; Donnat, Claire Donnat ; Sommer, Stefan Horst. / ICLR 2022 Challenge for Computational Geometry & Topology : Design and Results. Paper præsenteret ved ICLR 2022 Workshop on Geometrical and Topological Representation Learnings - ICLR 2022
, Virtual.8 s.

Bibtex

@conference{30d308c6115f4d559c6956f1cfc5ee6b,
title = "ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results",
abstract = "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 competition asked participants to provide implementations of machine learning algorithms on manifolds that would respect the API of the open-source software Geomstats (manifold part) and Scikit-Learn (machine learning part) or PyTorch. The challenge attracted seven teams in its two month duration. This paper describes the design of the challenge and summarizes its main findings.",
author = "Adele Myers and Sophia Sanborn and Donnat, {Claire Donnat} and Sommer, {Stefan Horst}",
year = "2022",
language = "English",
note = "ICLR 2022 Workshop on Geometrical and Topological Representation Learnings - ICLR 2022<br/> ; Conference date: 29-04-2022 Through 29-04-2022",

}

RIS

TY - CONF

T1 - ICLR 2022 Challenge for Computational Geometry & Topology

T2 - ICLR 2022 Workshop on Geometrical and Topological Representation Learnings - ICLR 2022<br/>

AU - Myers, Adele

AU - Sanborn, Sophia

AU - Donnat, Claire Donnat

AU - Sommer, Stefan Horst

PY - 2022

Y1 - 2022

N2 - 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 competition asked participants to provide implementations of machine learning algorithms on manifolds that would respect the API of the open-source software Geomstats (manifold part) and Scikit-Learn (machine learning part) or PyTorch. The challenge attracted seven teams in its two month duration. This paper describes the design of the challenge and summarizes its main findings.

AB - 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 competition asked participants to provide implementations of machine learning algorithms on manifolds that would respect the API of the open-source software Geomstats (manifold part) and Scikit-Learn (machine learning part) or PyTorch. The challenge attracted seven teams in its two month duration. This paper describes the design of the challenge and summarizes its main findings.

M3 - Paper

Y2 - 29 April 2022 through 29 April 2022

ER -

ID: 316672675