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Mathilde Papillon
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2020 – today
- 2024
- [i8]Mustafa Hajij, Mathilde Papillon, Florian Frantzen
, Jens Agerberg, Ibrahem AlJabea, Rubén Ballester, Claudio Battiloro, Guillermo Bernárdez, Tolga Birdal, Aiden Brent, Peter Chin, Sergio Escalera, Simone Fiorellino, Odin Hoff Gardaa, Gurusankar Gopalakrishnan, Devendra Govil, Josef Hoppe, Maneel Reddy Karri, Jude Khouja, Manuel Lecha, Neal Livesay, Jan Meißner, Soham Mukherjee
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains. CoRR abs/2402.02441 (2024) - [i7]Rubén Ballester, Pablo Hernández-García, Mathilde Papillon, Claudio Battiloro, Nina Miolane, Tolga Birdal, Carles Casacuberta, Sergio Escalera, Mustafa Hajij:
Attending to Topological Spaces: The Cellular Transformer. CoRR abs/2405.14094 (2024) - [i6]Sophia Sanborn, Johan Mathe, Mathilde Papillon, Domas Buracas, Hansen Lillemark, Christian Shewmake, Abby Bertics, Xavier Pennec, Nina Miolane:
Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures. CoRR abs/2407.09468 (2024) - [i5]Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree P. Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain. CoRR abs/2409.05211 (2024) - 2023
- [c3]Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn:
Preface. TAG-ML 2023: 1-2 - [c2]Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou
ICML 2023 Topological Deep Learning Challenge: Design and Results. TAG-ML 2023: 3-8 - [e1]Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn:
Topological, Algebraic and Geometric Learning Workshops 2023, 28 July 2023, Honolulu, HI, USA. Proceedings of Machine Learning Research 221, PMLR 2023 [contents] - [i4]Mathilde Papillon, Sophia Sanborn
Architectures of Topological Deep Learning: A Survey on Topological Neural Networks. CoRR abs/2304.10031 (2023) - [i3]Mathilde Papillon, Mustafa Hajij, Florian Frantzen, Josef Hoppe, Helen Jenne, Johan Mathe, Audun Myers, Theodore Papamarkou, Michael T. Schaub, Ghada Zamzmi, Tolga Birdal, Tamal K. Dey, Tim Doster, Tegan Emerson, Gurusankar Gopalakrishnan, Devendra Govil, Vincent P. Grande, Aldo Guzmán-Sáenz, Henry Kvinge, Neal Livesay, Jan Meissner, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Maneel Reddy Karri, Paul Rosen, Sophia Sanborn
ICML 2023 Topological Deep Learning Challenge : Design and Results. CoRR abs/2309.15188 (2023) - 2022
- [c1]Mathilde Papillon
PirouNet: Creating Dance Through Artist-Centric Deep Learning. ArtsIT 2022: 447-465 - [i2]Mathilde Papillon, Mariel Pettee, Nina Miolane
PirouNet: Creating Intentional Dance with Semi-Supervised Conditional Recurrent Variational Autoencoders. CoRR abs/2207.12126 (2022) - [i1]Mathilde Papillon, Mariel Pettee, Nina Miolane:
Intentional Choreography with Semi-Supervised Recurrent VAEs. CoRR abs/2209.10010 (2022)
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