Institution
Korea University
Education•Seoul, South Korea•
About: Korea University is a education organization based out in Seoul, South Korea. It is known for research contribution in the topics: Population & Thin film. The organization has 39756 authors who have published 82424 publications receiving 1860927 citations. The organization is also known as: Bosung College & Bosung Professional College.
Topics: Population, Thin film, Catalysis, Large Hadron Collider, Cancer
Papers published on a yearly basis
Papers
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TL;DR: The higher enzyme activities produced by A. niger KK2 is a significant advantage from the viewpoint of practical saccharification reaction and might be applied to pulp and paper industry, feed industry and chemical industry.
428 citations
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01 Jan 2019
TL;DR: This chapter gives a concise introduction to LRP with a discussion of how to implement propagation rules easily and efficiently, how the propagation procedure can be theoretically justified as a ‘deep Taylor decomposition’, how to choose the propagation rules at each layer to deliver high explanation quality, and how LRP can be extended to handle a variety of machine learning scenarios beyond deep neural networks.
Abstract: For a machine learning model to generalize well, one needs to ensure that its decisions are supported by meaningful patterns in the input data. A prerequisite is however for the model to be able to explain itself, e.g. by highlighting which input features it uses to support its prediction. Layer-wise Relevance Propagation (LRP) is a technique that brings such explainability and scales to potentially highly complex deep neural networks. It operates by propagating the prediction backward in the neural network, using a set of purposely designed propagation rules. In this chapter, we give a concise introduction to LRP with a discussion of (1) how to implement propagation rules easily and efficiently, (2) how the propagation procedure can be theoretically justified as a ‘deep Taylor decomposition’, (3) how to choose the propagation rules at each layer to deliver high explanation quality, and (4) how LRP can be extended to handle a variety of machine learning scenarios beyond deep neural networks.
428 citations
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TL;DR: In this paper, the authors use the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015.
427 citations
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TL;DR: In this paper, the authors investigated how output relates to the stock of human capital, measured by overall years of schooling as well as by the composition of educational attainment of workers at various levels of education.
Abstract: Our panel data set on educational attainment has been updated for 146 countries from 1950 to 2010. The data are disaggregated by sex and by 5-year age intervals. We have improved the accuracy of estimation by using information from consistent census data, disaggregated by age group, along with new estimates of mortality rates and completion rates by age and education level. We use these new data to investigate how output relates to the stock of human capital, measured by overall years of schooling as well as by the composition of educational attainment of workers at various levels of education. We find schooling has a significantly positive effect on output. After controlling for the simultaneous determination of human capital and output, by using the 10-year lag of parents' education as an instrument variable (IV) for the current level of education, the estimated rate-of-return to an additional year of schooling ranges from 5% to 12%, close to typical Mincerian return estimates found in the labor literature.
427 citations
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TL;DR: It is concluded that PRMT1 contributes the major type I protein arginine methyltransferase enzyme activity present in mammalian cells and tissues.
427 citations
Authors
Showing all 40083 results
Name | H-index | Papers | Citations |
---|---|---|---|
Anil K. Jain | 183 | 1016 | 192151 |
Hyun-Chul Kim | 176 | 4076 | 183227 |
Yongsun Kim | 156 | 2588 | 145619 |
Jongmin Lee | 150 | 2257 | 134772 |
Byung-Sik Hong | 146 | 1557 | 105696 |
Daniel S. Berman | 141 | 1363 | 86136 |
Christof Koch | 141 | 712 | 105221 |
David Y. Graham | 138 | 1047 | 80886 |
Suyong Choi | 135 | 1495 | 97053 |
Rudolph E. Tanzi | 135 | 638 | 85376 |
Sung Keun Park | 133 | 1567 | 96933 |
Tae Jeong Kim | 132 | 1420 | 93959 |
Robert S. Brown | 130 | 1243 | 65822 |
Mohammad Khaja Nazeeruddin | 129 | 646 | 85630 |
Klaus-Robert Müller | 129 | 764 | 79391 |