Zobrazeno 1 - 10
of 20 631
pro vyhledávání: '"Sanborn"'
Autor:
Mineault, Patrick, Zanichelli, Niccolò, Peng, Joanne Zichen, Arkhipov, Anton, Bingham, Eli, Jara-Ettinger, Julian, Mackevicius, Emily, Marblestone, Adam, Mattar, Marcelo, Payne, Andrew, Sanborn, Sophia, Schroeder, Karen, Tavares, Zenna, Tolias, Andreas
As AI systems become increasingly powerful, the need for safe AI has become more pressing. Humans are an attractive model for AI safety: as the only known agents capable of general intelligence, they perform robustly even under conditions that deviat
Externí odkaz:
http://arxiv.org/abs/2411.18526
Autor:
Liebhold, Andrew M., Turner, Rebecca M., Bartlett, Charles R., Bertelsmeier, Cleo, Blake, Rachael E., Brockerhoff, Eckehard G., Causton, Charlotte E., Matsunaga, Janis N., McKamey, Stuart H., Nahrung, Helen F., Owen, Christopher L., Pureswaran, Deepa S., Roques, Alain, Schneider, Scott A., Sanborn, Allen F., Yamanaka, Takehiko
Publikováno v:
Diversity and Distributions, 2024 Dec 01. 30(12), 1-12.
Externí odkaz:
https://www.jstor.org/stable/48798748
Publikováno v:
Neuropsychiatric Disease and Treatment, Vol Volume 16, Pp 2765-2777 (2020)
Victoria Sanborn,1 M Andrea Azcarate-Peril,2 John Updegraff,1 Lisa Manderino,1 John Gunstad1,3 1Department of Psychological Sciences, Kent State University, Kent, OH, USA; 2Department of Cell Biology and Physiology and Microbiome Core Facility, UNC S
Externí odkaz:
https://doaj.org/article/5b6422fde688428ca8dadcca443b0cc3
Autor:
Sanborn, Sophia, Mathe, Johan, Papillon, Mathilde, Buracas, Domas, Lillemark, Hansen J, Shewmake, Christian, Bertics, Abby, Pennec, Xavier, Miolane, Nina
The enduring legacy of Euclidean geometry underpins classical machine learning, which, for decades, has been primarily developed for data lying in Euclidean space. Yet, modern machine learning increasingly encounters richly structured data that is in
Externí odkaz:
http://arxiv.org/abs/2407.09468
An important problem in signal processing and deep learning is to achieve \textit{invariance} to nuisance factors not relevant for the task. Since many of these factors are describable as the action of a group $G$ (e.g. rotations, translations, scali
Externí odkaz:
http://arxiv.org/abs/2407.07655
In this work, we formally prove that, under certain conditions, if a neural network is invariant to a finite group then its weights recover the Fourier transform on that group. This provides a mathematical explanation for the emergence of Fourier fea
Externí odkaz:
http://arxiv.org/abs/2312.08550
Autor:
Xie, Jingxu, Zhang, Zuocheng, Zhang, Haodong, Nagarajan, Vikram, Zhao, Wenyu, Kim, Haleem, Sanborn, Collin, Qi, Ruishi, Chen, Sudi, Kahn, Salman, Watanabe, Kenji, Taniguchi, Takashi, Zettl, Alex, Crommie, Michael, Analytis, James, Wang, Feng
Advanced microelectronics in the future may require semiconducting channel materials beyond silicon. Two-dimensional (2D) semiconductors, characterized by their atomically thin thickness, hold immense promise for high-performance electronic devices a
Externí odkaz:
http://arxiv.org/abs/2312.04849
Autor:
Correa, Carlos G., Sanborn, Sophia, Ho, Mark K., Callaway, Frederick, Daw, Nathaniel D., Griffiths, Thomas L.
Human behavior is often assumed to be hierarchically structured, made up of abstract actions that can be decomposed into concrete actions. However, behavior is typically measured as a sequence of actions, which makes it difficult to infer its hierarc
Externí odkaz:
http://arxiv.org/abs/2311.18644