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is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2402.02441">arXiv:2402.02441</a> <span> [<a href="https://arxiv.org/pdf/2402.02441">pdf</a>, <a href="https://arxiv.org/format/2402.02441">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Mathematical Software">cs.MS</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computation">stat.CO</span> </div> </div> <p class="title is-5 mathjax"> TopoX: A Suite of Python Packages for Machine Learning on Topological Domains </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Hajij%2C+M">Mustafa Hajij</a>, <a href="/search/cs?searchtype=author&query=Papillon%2C+M">Mathilde Papillon</a>, <a href="/search/cs?searchtype=author&query=Frantzen%2C+F">Florian Frantzen</a>, <a href="/search/cs?searchtype=author&query=Agerberg%2C+J">Jens Agerberg</a>, <a href="/search/cs?searchtype=author&query=AlJabea%2C+I">Ibrahem AlJabea</a>, <a href="/search/cs?searchtype=author&query=Ballester%2C+R">Ruben Ballester</a>, <a href="/search/cs?searchtype=author&query=Battiloro%2C+C">Claudio Battiloro</a>, <a href="/search/cs?searchtype=author&query=Bern%C3%A1rdez%2C+G">Guillermo Bern谩rdez</a>, <a href="/search/cs?searchtype=author&query=Birdal%2C+T">Tolga Birdal</a>, <a href="/search/cs?searchtype=author&query=Brent%2C+A">Aiden Brent</a>, <a href="/search/cs?searchtype=author&query=Chin%2C+P">Peter Chin</a>, <a href="/search/cs?searchtype=author&query=Escalera%2C+S">Sergio Escalera</a>, <a href="/search/cs?searchtype=author&query=Fiorellino%2C+S">Simone Fiorellino</a>, <a href="/search/cs?searchtype=author&query=Gardaa%2C+O+H">Odin Hoff Gardaa</a>, <a href="/search/cs?searchtype=author&query=Gopalakrishnan%2C+G">Gurusankar Gopalakrishnan</a>, <a href="/search/cs?searchtype=author&query=Govil%2C+D">Devendra Govil</a>, <a href="/search/cs?searchtype=author&query=Hoppe%2C+J">Josef Hoppe</a>, <a href="/search/cs?searchtype=author&query=Karri%2C+M+R">Maneel Reddy Karri</a>, <a href="/search/cs?searchtype=author&query=Khouja%2C+J">Jude Khouja</a>, <a href="/search/cs?searchtype=author&query=Lecha%2C+M">Manuel Lecha</a>, <a href="/search/cs?searchtype=author&query=Livesay%2C+N">Neal Livesay</a>, <a href="/search/cs?searchtype=author&query=Mei%C3%9Fner%2C+J">Jan Mei脽ner</a>, <a href="/search/cs?searchtype=author&query=Mukherjee%2C+S">Soham Mukherjee</a>, <a href="/search/cs?searchtype=author&query=Nikitin%2C+A">Alexander Nikitin</a>, <a href="/search/cs?searchtype=author&query=Papamarkou%2C+T">Theodore Papamarkou</a> , et al. (18 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2402.02441v4-abstract-short" style="display: inline;"> We introduce TopoX, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: hypergraphs, simplicial, cellular, path and combinatorial complexes. TopoX consists of three packages: TopoNetX facilitates constructing and computing on these domains, including working with nodes, edges and higher-order… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.02441v4-abstract-full').style.display = 'inline'; document.getElementById('2402.02441v4-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2402.02441v4-abstract-full" style="display: none;"> We introduce TopoX, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: hypergraphs, simplicial, cellular, path and combinatorial complexes. TopoX consists of three packages: TopoNetX facilitates constructing and computing on these domains, including working with nodes, edges and higher-order cells; TopoEmbedX provides methods to embed topological domains into vector spaces, akin to popular graph-based embedding algorithms such as node2vec; TopoModelx is built on top of PyTorch and offers a comprehensive toolbox of higher-order message passing functions for neural networks on topological domains. The extensively documented and unit-tested source code of TopoX is available under MIT license at https://pyt-team.github.io/. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2402.02441v4-abstract-full').style.display = 'none'; document.getElementById('2402.02441v4-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 February, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 4 February, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2309.15188">arXiv:2309.15188</a> <span> [<a href="https://arxiv.org/pdf/2309.15188">pdf</a>, <a href="https://arxiv.org/format/2309.15188">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.5281/zenodo.7958513">10.5281/zenodo.7958513 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> ICML 2023 Topological Deep Learning Challenge : Design and Results </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Papillon%2C+M">Mathilde Papillon</a>, <a href="/search/cs?searchtype=author&query=Hajij%2C+M">Mustafa Hajij</a>, <a href="/search/cs?searchtype=author&query=Jenne%2C+H">Helen Jenne</a>, <a href="/search/cs?searchtype=author&query=Mathe%2C+J">Johan Mathe</a>, <a href="/search/cs?searchtype=author&query=Myers%2C+A">Audun Myers</a>, <a href="/search/cs?searchtype=author&query=Papamarkou%2C+T">Theodore Papamarkou</a>, <a href="/search/cs?searchtype=author&query=Birdal%2C+T">Tolga Birdal</a>, <a href="/search/cs?searchtype=author&query=Dey%2C+T">Tamal Dey</a>, <a href="/search/cs?searchtype=author&query=Doster%2C+T">Tim Doster</a>, <a href="/search/cs?searchtype=author&query=Emerson%2C+T">Tegan Emerson</a>, <a href="/search/cs?searchtype=author&query=Gopalakrishnan%2C+G">Gurusankar Gopalakrishnan</a>, <a href="/search/cs?searchtype=author&query=Govil%2C+D">Devendra Govil</a>, <a href="/search/cs?searchtype=author&query=Guzm%C3%A1n-S%C3%A1enz%2C+A">Aldo Guzm谩n-S谩enz</a>, <a href="/search/cs?searchtype=author&query=Kvinge%2C+H">Henry Kvinge</a>, <a href="/search/cs?searchtype=author&query=Livesay%2C+N">Neal Livesay</a>, <a href="/search/cs?searchtype=author&query=Mukherjee%2C+S">Soham Mukherjee</a>, <a href="/search/cs?searchtype=author&query=Samaga%2C+S+N">Shreyas N. Samaga</a>, <a href="/search/cs?searchtype=author&query=Ramamurthy%2C+K+N">Karthikeyan Natesan Ramamurthy</a>, <a href="/search/cs?searchtype=author&query=Karri%2C+M+R">Maneel Reddy Karri</a>, <a href="/search/cs?searchtype=author&query=Rosen%2C+P">Paul Rosen</a>, <a href="/search/cs?searchtype=author&query=Sanborn%2C+S">Sophia Sanborn</a>, <a href="/search/cs?searchtype=author&query=Walters%2C+R">Robin Walters</a>, <a href="/search/cs?searchtype=author&query=Agerberg%2C+J">Jens Agerberg</a>, <a href="/search/cs?searchtype=author&query=Barikbin%2C+S">Sadrodin Barikbin</a>, <a href="/search/cs?searchtype=author&query=Battiloro%2C+C">Claudio Battiloro</a> , et al. (31 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2309.15188v4-abstract-short" style="display: inline;"> This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competition asked participants to provide open-source implementations of topological neural networks from the literature by contributing to the python packages TopoNetX (data processing) and TopoModelX (deep learning). The chal… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2309.15188v4-abstract-full').style.display = 'inline'; document.getElementById('2309.15188v4-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2309.15188v4-abstract-full" style="display: none;"> This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competition asked participants to provide open-source implementations of topological neural networks from the literature by contributing to the python packages TopoNetX (data processing) and TopoModelX (deep learning). The challenge attracted twenty-eight qualifying submissions in its two-month duration. This paper describes the design of the challenge and summarizes its main findings. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2309.15188v4-abstract-full').style.display = 'none'; document.getElementById('2309.15188v4-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 26 September, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2023. </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>  </span> </div> </div> </main> <footer> <div class="columns is-desktop" role="navigation" aria-label="Secondary">  <div class="column"> <div class="columns"> <div 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