Sophia Sanborn

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 25

Top Topics

Computational Geometry

Scale Invariance

Top Venues

Publications

Simon Mataigne, Johan Mathe, Sophia Sanborn, Christopher Hillar, Nina Miolane
The Selective G-Bispectrum and its Inversion: Applications to G-Invariant Networks. CoRR (2024)
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 (2024)
Giovanni Luca Marchetti, Christopher J. Hillar, Danica Kragic, Sophia Sanborn
Harmonics of Learning: Universal Fourier Features Emerge in Invariant Networks. COLT (2024)
Sophia Sanborn, Nina Miolane
A General Framework for Robust G-Invariance in G-Equivariant Networks. CoRR (2023)
Giovanni Luca Marchetti, Christopher Hillar, Danica Kragic, Sophia Sanborn
Harmonics of Learning: Universal Fourier Features Emerge in Invariant Networks. CoRR (2023)
Francisco Acosta, Sophia Sanborn, Khanh Dao Duc, Manu S. Madhav, Nina Miolane
Quantifying Extrinsic Curvature in Neural Manifolds. CVPR Workshops (2023)
Sophia Sanborn, Nina Miolane
A General Framework for Robust G-Invariance in G-Equivariant Networks. NeurIPS (2023)
Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane
ICML 2023 Topological Deep Learning Challenge: Design and Results. TAG-ML (2023)
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 Meisner, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Maneel Reddy Karri, Paul Rosen, Sophia Sanborn, Michael Scholkemper, Robin Walters, Jens Agerberg, Georg Bökman, Sadrodin Barikbin, Claudio Battiloro, Gleb Bazhenov, Guillermo Bernárdez, Aiden Brent, Sergio Escalera, Simone Fiorellino, Dmitrii Gavrilev, Mohammed Hassanin, Paul Häusner, Odin Hoff Gardaa, Abdelwahed Khamis, Manuel Lecha, German Magai, Tatiana Malygina, Pavlo Melnyk, et al.
ICML 2023 Topological Deep Learning Challenge : Design and Results. CoRR (2023)
Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
Preface. TAG-ML (2023)
David A. Klindt, Sophia Sanborn, Francisco Acosta, Frédéric Poitevin, Nina Miolane
Identifying Interpretable Visual Features in Artificial and Biological Neural Systems. CoRR (2023)
Sophia Sanborn, Christian Shewmake, Bruno A. Olshausen, Christopher J. Hillar
Bispectral Neural Networks. ICLR (2023)
Mathilde Papillon, Sophia Sanborn, Mustafa Hajij, Nina Miolane
Architectures of Topological Deep Learning: A Survey on Topological Neural Networks. CoRR (2023)
Carlos G. Correa, Sophia Sanborn, Mark K. Ho, Frederick Callaway, Nathaniel D. Daw, Thomas L. Griffiths
Exploring the hierarchical structure of human plans via program generation. CoRR (2023)
Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Umberto Lupo, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David Klindt, Erik Hermansen, Melvin Vaupel, Benjamin Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava Yazdani, Christoph von Tycowicz, Nina Miolane
ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results. CoRR (2022)
Sophia Sanborn, Christian Shewmake, Simone Azeglio, Arianna Di Bernardo, Nina Miolane
Preface. NeurReps (2022)
Sophia Sanborn, Christian Shewmake, Bruno A. Olshausen, Christopher Hillar
Bispectral Neural Networks. CoRR (2022)
Edward Paxon Frady, Sophia Sanborn, Sumit Bam Shrestha, Daniel Ben Dayan Rubin, Garrick Orchard, Friedrich T. Sommer, Mike Davies
Efficient Neuromorphic Signal Processing with Resonator Neurons. J. Signal Process. Syst. 94 (10) (2022)
Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane
ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. TAG-ML (2022)
Garrick Orchard, Edward Paxon Frady, Daniel Ben Dayan Rubin, Sophia Sanborn, Sumit Bam Shrestha, Friedrich T. Sommer, Mike Davies
Efficient Neuromorphic Signal Processing with Loihi 2. CoRR (2021)
Garrick Orchard, Edward Paxon Frady, Daniel Ben Dayan Rubin, Sophia Sanborn, Sumit Bam Shrestha, Friedrich T. Sommer, Mike Davies
Efficient Neuromorphic Signal Processing with Loihi 2. SiPS (2021)
Joseph L. Austerweil, Sophia Sanborn, Thomas L. Griffiths
Learning How to Generalize. Cogn. Sci. 43 (8) (2019)
Sophia Sanborn, David Bourgin, Michael Chang, Tom Griffiths
Representational efficiency outweighs action efficiency in human program induction. CogSci (2018)
Sophia Sanborn, David D. Bourgin, Michael Chang, Thomas L. Griffiths
Representational efficiency outweighs action efficiency in human program induction. CoRR (2018)
Rebecca Zhu, Jean-Rémy Hochmann, Sophia Sanborn, Susan Carey
Representations of Entropy and of the Relations Same and Different Early in Human Development. CogSci (2016)