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Institution

National University of Singapore

EducationSingapore, Singapore
About: National University of Singapore is a education organization based out in Singapore, Singapore. It is known for research contribution in the topics: Population & Membrane. The organization has 74269 authors who have published 165426 publications receiving 5474934 citations. The organization is also known as: NUS & Universiti Kebangsaan Singapura.


Papers
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Journal ArticleDOI
TL;DR: A fast, greedy algorithm is derived that can learn deep, directed belief networks one layer at a time, provided the top two layers form an undirected associative memory.
Abstract: We show how to use "complementary priors" to eliminate the explaining-away effects that make inference difficult in densely connected belief nets that have many hidden layers. Using complementary priors, we derive a fast, greedy algorithm that can learn deep, directed belief networks one layer at a time, provided the top two layers form an undirected associative memory. The fast, greedy algorithm is used to initialize a slower learning procedure that fine-tunes the weights using a contrastive version of the wake-sleep algorithm. After fine-tuning, a network with three hidden layers forms a very good generative model of the joint distribution of handwritten digit images and their labels. This generative model gives better digit classification than the best discriminative learning algorithms. The low-dimensional manifolds on which the digits lie are modeled by long ravines in the free-energy landscape of the top-level associative memory, and it is easy to explore these ravines by using the directed connections to display what the associative memory has in mind.

15,055 citations

Journal ArticleDOI
Rafael Lozano1, Mohsen Naghavi1, Kyle J Foreman2, Stephen S Lim1  +192 moreInstitutions (95)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2010 aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex, using the Cause of Death Ensemble model.

11,809 citations

Journal ArticleDOI
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.

10,401 citations

Journal ArticleDOI
25 Nov 2009-Cell
TL;DR: The mesenchymal state is associated with the capacity of cells to migrate to distant organs and maintain stemness, allowing their subsequent differentiation into multiple cell types during development and the initiation of metastasis.

8,642 citations

Journal ArticleDOI
TL;DR: This Review describes how the tunable electronic structure of TMDs makes them attractive for a variety of applications, as well as electrically active materials in opto-electronics.
Abstract: Ultrathin two-dimensional nanosheets of layered transition metal dichalcogenides (TMDs) are fundamentally and technologically intriguing. In contrast to the graphene sheet, they are chemically versatile. Mono- or few-layered TMDs - obtained either through exfoliation of bulk materials or bottom-up syntheses - are direct-gap semiconductors whose bandgap energy, as well as carrier type (n- or p-type), varies between compounds depending on their composition, structure and dimensionality. In this Review, we describe how the tunable electronic structure of TMDs makes them attractive for a variety of applications. They have been investigated as chemically active electrocatalysts for hydrogen evolution and hydrosulfurization, as well as electrically active materials in opto-electronics. Their morphologies and properties are also useful for energy storage applications such as electrodes for Li-ion batteries and supercapacitors.

7,903 citations


Authors

Showing all 74987 results

NameH-indexPapersCitations
Albert Hofman2672530321405
Ronald Klein1941305149140
Jie Zhang1784857221720
Kay-Tee Khaw1741389138782
Barry Halliwell173662159518
Yang Yang1712644153049
Richard H. Friend1691182140032
Gang Chen1673372149819
Charles M. Lieber165521132811
Hua Zhang1631503116769
Tien Yin Wong1601880131830
Barbara E.K. Klein16085693319
Pete Smith1562464138819
Johan G. Eriksson1561257123325
Xiang Zhang1541733117576
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023348
20221,287
202112,381
202012,162
201910,309
20189,446