Zobrazeno 1 - 10
of 165 239
pro vyhledávání: '"Andrew, M"'
Autor:
Jailani, Javith Mohammed, Luu, Amanda, Salvosa, Elizabeth, Clegg, Charlotte, Kamalon, Vishnupriya P., Nasrollahi, Bahareh, Valitova, Irina, Meier, Sebastian B., Shore, Andrew M., Hamadani, Behrang H., Pecunia, Vincenzo
Indoor photovoltaics (IPVs) provide an increasingly promising solution for powering Internet-of-Things smart devices, which has led to a surge in IPV research and the development of new IPV technologies. However, the diverse lighting scenarios adopte
Externí odkaz:
http://arxiv.org/abs/2408.13485
Most music widely consumed in Western Countries contains song lyrics, with U.S. samples reporting almost all of their song libraries contain lyrics. In parallel, social science theory suggests that personal values - the abstract goals that guide our
Externí odkaz:
http://arxiv.org/abs/2408.12694
Autor:
Zhu, Menglin, Xu, Michael, Qi, Yubo, Gilgenbach, Colin, Kim, Jieun, Zhang, Jiahao, Denzer, Bridget R., Martin, Lane W., Rappe, Andrew M., LeBeau, James M.
Introducing structural and/or chemical heterogeneity into otherwise ordered crystals can dramatically alter material properties. Lead-based relaxor ferroelectrics are a prototypical example, with decades of investigation having connected chemical and
Externí odkaz:
http://arxiv.org/abs/2408.11685
Training Large Language Models (LLMs) incurs substantial data-related costs, motivating the development of data-efficient training methods through optimised data ordering and selection. Human-inspired learning strategies, such as curriculum learning,
Externí odkaz:
http://arxiv.org/abs/2408.07888
Autor:
Nelsen, Nicholas H., Stuart, Andrew M.
Publikováno v:
SIAM Review Vol. 66 No. 3 (2024) pp. 535-571
Supervised operator learning centers on the use of training data, in the form of input-output pairs, to estimate maps between infinite-dimensional spaces. It is emerging as a powerful tool to complement traditional scientific computing, which may oft
Externí odkaz:
http://arxiv.org/abs/2408.06526
Autor:
Low, Andrew M.
This research study uses hierarchical logistic regression to identify predictors of first-class STEM degree outcomes at a research-intensive Russell Group university in the UK between 2012 and 2022. By building a multivariate binary logistic model wi
Externí odkaz:
http://arxiv.org/abs/2408.05853
Autoencoders have found widespread application, in both their original deterministic form and in their variational formulation (VAEs). In scientific applications it is often of interest to consider data that are comprised of functions; the same persp
Externí odkaz:
http://arxiv.org/abs/2408.01362
Capturing the inter-dependencies among multiple types of clinically-critical events is critical not only to accurate future event prediction, but also to better treatment planning. In this work, we propose a deep latent state-space generative model t
Externí odkaz:
http://arxiv.org/abs/2407.19371
We propose to meta-learn an a self-supervised patient trajectory forecast learning rule by meta-training on a meta-objective that directly optimizes the utility of the patient representation over the subsequent clinical outcome prediction. This meta-
Externí odkaz:
http://arxiv.org/abs/2407.19359
Autor:
Graff, Andrew M., Humphreys, Todd E.
This paper presents bounds, estimators, and signal design strategies for exploiting both known pilot resources and unknown data payload resources in time-of-arrival (TOA)-based positioning systems with orthogonal frequency-division multiplexing (OFDM
Externí odkaz:
http://arxiv.org/abs/2407.19106