Zobrazeno 1 - 10
of 725
pro vyhledávání: '"Tomkins Andrew"'
Autor:
Rashtchian, Cyrus, Herrmann, Charles, Ferng, Chun-Sung, Chakrabarti, Ayan, Krishnan, Dilip, Sun, Deqing, Juan, Da-Cheng, Tomkins, Andrew
Probes are small networks that predict properties of underlying data from embeddings, and they provide a targeted, effective way to illuminate the information contained in embeddings. While analysis through the use of probes has become standard in NL
Externí odkaz:
http://arxiv.org/abs/2307.05610
Publikováno v:
Proceedings of The 26th International Conference on Artificial Intelligence and Statistics (AISTATS), 2023, pages 4757-4767, volume 206
In this work we consider the problem of fitting Random Utility Models (RUMs) to user choices. Given the winner distributions of the subsets of size $k$ of a universe, we obtain a polynomial-time algorithm that finds the RUM that best approximates the
Externí odkaz:
http://arxiv.org/abs/2305.13283
Autor:
Goldani Marcelo Zubaran, Giugliani Elsa Regina Justo, Scanlon Thomas, Rosa Humberto, Castilhos Kelli, Feldens Letícia, Tomkins Andrew
Publikováno v:
Revista de Saúde Pública, Vol 37, Iss 5, Pp 552-558 (2003)
OBJECTIVE: Voluntary HIV counseling and testing are provided to all Brazilian pregnant women with the purpose of reducing mother-to-child HIV transmission. The purpose of the study was to assess characteristics of HIV testing and identify factors ass
Externí odkaz:
https://doaj.org/article/6a2822e172ee4145a5e9400d0d572e3e
Autor:
Goldani Marcelo Zubaran, Barbieri Marco Antonio, Bettiol Heloisa, Barbieri Marisa Ramos, Tomkins Andrew
Publikováno v:
Revista de Saúde Pública, Vol 35, Iss 3, Pp 256-261 (2001)
OBJECTIVE: Data from municipal databases can be used to plan interventions aimed at reducing inequities in health care. The objective of the study was to determine the distribution of infant mortality according to an urban geoeconomic classification
Externí odkaz:
https://doaj.org/article/d31beab9c7f64a83a8b71fd42c087039
Publikováno v:
Cadernos de Saúde Pública, Vol 16, Iss 4, Pp 1041-1047 (2000)
This study focused on changes in demographic, social, and health-care patterns and pregnancy outcome related to maternal age from 1978-79 to 1994 in Ribeirão Preto, São Paulo State, Brazil. Information on pregnancy outcome was obtained from two coh
Externí odkaz:
https://doaj.org/article/8286afad1ac94efdaed183307344aa92
Autor:
Arora, Neha, Cabannes, Theophile, Ganapathy, Sanjay, Li, Yechen, McAfee, Preston, Nunkesser, Marc, Osorio, Carolina, Tomkins, Andrew, Tsogsuren, Iveel
Google Maps uses current and historical traffic trends to provide routes to drivers. In this paper, we use microscopic traffic simulation to quantify the improvements to both travel time and CO$_2$ emissions from Google Maps real-time navigation. A c
Externí odkaz:
http://arxiv.org/abs/2111.03426
Autor:
Arora, Neha, Chen, Yi-fan, Ganapathy, Sanjay, Li, Yechen, Lin, Ziheng, Osorio, Carolina, Tomkins, Andrew, Tsogsuren, Iveel
Metropolitan scale vehicular traffic modeling is used by a variety of private and public sector urban mobility stakeholders to inform the design and operations of road networks. High-resolution stochastic traffic simulators are increasingly used to d
Externí odkaz:
http://arxiv.org/abs/2109.11392
Autor:
Fougerouse, Denis, Reddy, Steven M., Sumail, Brugger, Joël, Thébaud, Nicolas, Rickard, William D.A., Yang, Lin, Quadir, Zakaria, Roberts, Malcolm P., Tomkins, Andrew G., Martin, Laure, Petrella, Laura, Voisey, Christopher R.
Publikováno v:
In Geochimica et Cosmochimica Acta 1 June 2024 374:136-145
Autor:
Lu, Chun-Ta, Zeng, Yun, Juan, Da-Cheng, Fan, Yicheng, Li, Zhe, Dlabal, Jan, Chen, Yi-Ting, Gopalan, Arjun, Heydon, Allan, Ferng, Chun-Sung, Miyara, Reah, Fuxman, Ariel, Peng, Futang, Li, Zhen, Duerig, Tom, Tomkins, Andrew
In this work, we propose CARLS, a novel framework for augmenting the capacity of existing deep learning frameworks by enabling multiple components -- model trainers, knowledge makers and knowledge banks -- to concertedly work together in an asynchron
Externí odkaz:
http://arxiv.org/abs/2105.12849
Recent studies have indicated that Graph Convolutional Networks (GCNs) act as a \emph{low pass} filter in spectral domain and encode smoothed node representations. In this paper, we consider their opposite, namely Graph Deconvolutional Networks (GDNs
Externí odkaz:
http://arxiv.org/abs/2012.11898