Zobrazeno 1 - 10
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pro vyhledávání: '"Bruce, D. A."'
Autor:
Popp, Bruce D.
J. Willard Gibbs published a book in 1902 on statistical mechanics that quickly received significant attention from his contemporaries because of the reputation that he had secured with his prior work on thermodynamics. People reading Gibbs's book we
Externí odkaz:
http://arxiv.org/abs/2412.11425
A driving force behind the diverse applicability of modern machine learning is the ability to extract meaningful features across many sources. However, many practical domains involve data that are non-identically distributed across sources, and stati
Externí odkaz:
http://arxiv.org/abs/2410.11227
Autor:
Schobel, Bruce D. bdschobel@aol.com
Publikováno v:
Journal of Financial Service Professionals. Nov2024, Vol. 78 Issue 6, p35-39. 5p.
Representation learning is a powerful tool that enables learning over large multitudes of agents or domains by enforcing that all agents operate on a shared set of learned features. However, many robotics or controls applications that would benefit f
Externí odkaz:
http://arxiv.org/abs/2407.05781
Autor:
Scott, Bruce D.
The issue of finite magnetic compressibility in low-beta magnetised plasmas is considered within the gyrokinetic description. The gauge transformation method of Littlejohn is used to obtain a Lagrangian which contains this effect additionally. The fi
Externí odkaz:
http://arxiv.org/abs/2405.18985
Model-based reinforcement learning is an effective approach for controlling an unknown system. It is based on a longstanding pipeline familiar to the control community in which one performs experiments on the environment to collect a dataset, uses th
Externí odkaz:
http://arxiv.org/abs/2404.09030
Large-scale robotic policies trained on data from diverse tasks and robotic platforms hold great promise for enabling general-purpose robots; however, reliable generalization to new environment conditions remains a major challenge. Toward addressing
Externí odkaz:
http://arxiv.org/abs/2403.18222
Model-assisted, two-stage forest survey sampling designs provide a means to combine airborne remote sensing data, collected in a sampling mode, with field plot data to increase the precision of national forest inventory estimates, while maintaining i
Externí odkaz:
http://arxiv.org/abs/2402.11029
The strategy of pre-training a large model on a diverse dataset, then fine-tuning for a particular application has yielded impressive results in computer vision, natural language processing, and robotic control. This strategy has vast potential in ad
Externí odkaz:
http://arxiv.org/abs/2401.00073
Autor:
Ross C. Gruber, Gregory S. Wirak, Anna S. Blazier, Lan Lee, Michael R. Dufault, Nellwyn Hagan, Nathalie Chretien, Michael LaMorte, Timothy R. Hammond, Agnes Cheong, Sean K. Ryan, Andrew Macklin, Mindy Zhang, Nilesh Pande, Evis Havari, Timothy J. Turner, Anthony Chomyk, Emilie Christie, Bruce D. Trapp, Dimitry Ofengeim
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-17 (2024)
Abstract Neuroinflammation in the central nervous system (CNS), driven largely by resident phagocytes, has been proposed as a significant contributor to disability accumulation in multiple sclerosis (MS) but has not been addressed therapeutically. Br
Externí odkaz:
https://doaj.org/article/7240258f9fe44a898fcf295ec6f91164