| 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 | 247 | 2021 |
| 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 | 70 | 2017 |
| 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 | 68 | 2017 |
| 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 | 51 | 2023 |
| 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 | 35 | 2022 |
| Learning how to generalize JL Austerweil, S Sanborn, TL Griffiths Cognitive science 43 (8), e12777, 2019 | 24 | 2019 |
| Bispectral Neural Networks S Sanborn, C Shewmake, B Olshausen, C Hillar International Conference on Learning Representations (ICLR), 2023 | 20 | 2023 |
| 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 | 19 | 2022 |
| 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 | 19 | 2021 |
| 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 | 14 | 2024 |
| Representational efficiency outweighs action efficiency in human program induction S Sanborn, DD Bourgin, M Chang, TL Griffiths Cognitive Science Society (CSS), 2018 | 10 | 2018 |
| 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 | 7 | 2023 |
| 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 | 7 | 2023 |
| Human priors in hierarchical program induction MK Ho, S Sanborn, F Callaway, D Bourgin, T Griffiths Computational Cognitive Neuroscience (CCN), 2018 | 7 | 2018 |
| 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 | 5 | 2025 |
| 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 | 5 | 2023 |
| 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 | 4 | 2024 |
| 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 | 4 | 2022 |
Nina MiolaneAssistant Professor at UC Santa BarbaraVerified email at ucsb.edu