Прати
Sophia Sanborn
Sophia Sanborn
Верификована је имејл адреса на stanford.edu - Почетна страница
Наслов
Навело
Навело
Година
Efficient Neuromorphic Signal Processing with Loihi 2
G Orchard, EP Frady, DB Dayan Rubin, S Sanborn, SB Shrestha, ...
IEEE Workshop on Signal Processing Systems, 2021
2432021
Children’s representation of abstract relations in relational/array match-to-sample tasks
JR Hochmann, AS Tuerk, S Sanborn, R Zhu, R Long, M Dempster, ...
Cognitive psychology 99, 17-43, 2017
692017
What do you mean, no? Toddlers’ comprehension of logical “no” and “not”
R Feiman, S Mody, S Sanborn, S Carey
Language Learning and Development 13 (4), 430-450, 2017
662017
Architectures of topological deep learning: A survey of message-passing topological neural networks
M Papillon, S Sanborn, M Hajij, N Miolane
arXiv preprint arXiv:2304.10031, 2023
512023
Euclidean neural networks: e3nn
M Geiger, T Smidt, M Alby, BK Miller, W Boomsma, B Dice, K Lapchevskyi, ...
Preprint at https://doi. org/10.48550/arXiv 2207, 2022
352022
Learning how to generalize
JL Austerweil, S Sanborn, TL Griffiths
Cognitive science 43 (8), e12777, 2019
242019
Bispectral Neural Networks
S Sanborn, C Shewmake, B Olshausen, C Hillar
International Conference on Learning Representations (ICLR), 2023
202023
Efficient neuromorphic signal processing with resonator neurons
EP Frady, S Sanborn, SB Shrestha, DBD Rubin, G Orchard, FT Sommer, ...
Journal of Signal Processing Systems 94 (10), 917-927, 2022
192022
Efficient neuromorphic signal processing with loihi 2 2021 IEEE Workshop on Signal Processing Systems (SiPS)
G Orchard, EP Frady, DBD Rubin, S Sanborn, SB Shrestha, FT Sommer, ...
IEEE, 2021
192021
Euclidean neural networks: e3nn, April 2022
M Geiger, T Smidt, M Alby, BK Miller, W Boomsma, B Dice, K Lapchevskyi, ...
URL https://doi. org/10.5281/zenodo 6459381 (4), 0
16
Euclidean neural networks: e3nn, 2020
M Geiger, T Smidt, M Alby, BK Miller, W Boomsma, B Dice, K Lapchevskyi, ...
URL https://doi. org/10.5281/zenodo 5292912, 0
15
Harmonics of learning: Universal fourier features emerge in invariant networks
GL Marchetti, CJ Hillar, D Kragic, S Sanborn
The Thirty Seventh Annual Conference on Learning Theory, 3775-3797, 2024
122024
Representational efficiency outweighs action efficiency in human program induction
S Sanborn, DD Bourgin, M Chang, TL Griffiths
Cognitive Science Society (CSS), 2018
102018
Icml 2023 topological deep learning challenge: Design and results
M Papillon, M Hajij, A Myers, H Jenne, J Mathe, T Papamarkou, ...
Topological, Algebraic and Geometric Learning Workshops 2023, 3-8, 2023
72023
Quantifying extrinsic curvature in neural manifolds
F Acosta, S Sanborn, KD Duc, M Madhav, N Miolane
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
72023
Human priors in hierarchical program induction
MK Ho, S Sanborn, F Callaway, D Bourgin, T Griffiths
Computational Cognitive Neuroscience (CCN), 2018
72018
Exploring the hierarchical structure of human plans via program generation
CG Correa, S Sanborn, MK Ho, F Callaway, ND Daw, TL Griffiths
Cognition 255, 105990, 2025
52025
Beyond euclid: An illustrated guide to modern machine learning with geometric, topological, and algebraic structures
S Sanborn, J Mathe, M Papillon, D Buracas, HJ Lillemark, C Shewmake, ...
arXiv preprint arXiv:2407.09468, 2024
42024
Iclr 2022 challenge for computational geometry & topology: Design and results
A Myers, S Utpala, S Talbar, S Sanborn, C Shewmake, C Donnat, J Mathe, ...
Topological, Algebraic and Geometric Learning Workshops 2022, 269-276, 2022
42022
Identifying Interpretable Visual Features in Artificial and Biological Neural Systems
D Klindt, S Sanborn, F Acosta, F Poitevin, N Miolane
arXiv preprint: arXiv:2310.11431, 2023
32023
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