Institution
University of Massachusetts Amherst
Education•Amherst Center, Massachusetts, United States•
About: University of Massachusetts Amherst is a education organization based out in Amherst Center, Massachusetts, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 37274 authors who have published 83965 publications receiving 3834996 citations. The organization is also known as: UMass Amherst & Massachusetts State College.
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the authors investigated the large-scale control on the climate of the South American Altiplano using local observations, reanalysis data and general circulation model experiments and found that the climatic conditions on the Altiplano are closely related to the upper-air circulation, with an easterly zonal flow aloft favoring wet conditions and westerly flow causing dry conditions.
610 citations
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TL;DR: In vitro and in planta evaluations of silver indicated that both silver ions and nanoparticles influence colony formation of spores and disease progress of plant-pathogenic fungi, which is much greater with preventative application.
Abstract: Silver in ionic or nanoparticle forms has a high antimicrobial activity and is therefore widely used for various sterilization purposes including materials of medical devices and water san...
609 citations
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01 Jan 2013TL;DR: In this article, a matrix factorization model is used to learn latent feature vectors for entity tuples and relations in a universal schema, which has an almost unlimited set of relations (due to surface forms).
Abstract: © 2013 Association for Computational Linguistics. Traditional relation extraction predicts relations within some fixed and finite target schema. Machine learning approaches to this task require either manual annotation or, in the case of distant supervision, existing structured sources of the same schema. The need for existing datasets can be avoided by using a universal schema: the union of all involved schemas (surface form predicates as in OpenIE, and relations in the schemas of preexisting databases). This schema has an almost unlimited set of relations (due to surface forms), and supports integration with existing structured data (through the relation types of existing databases). To populate a database of such schema we present matrix factorization models that learn latent feature vectors for entity tuples and relations. We show that such latent models achieve substantially higher accuracy than a traditional classification approach. More importantly, by operating simultaneously on relations observed in text and in pre-existing structured DBs such as Freebase, we are able to reason about unstructured and structured data in mutually-supporting ways. By doing so our approach outperforms stateof- the-Art distant supervision.
609 citations
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TL;DR: In this paper, the spin and parity quantum numbers of the Higgs boson were studied based on the collision data collected by the ATLAS experiment at the LHC, and the results showed that the standard model spin-parity J(...
608 citations
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TL;DR: It is suggested that there is a functional role for variability in lower extremity segment coupling during locomotion and the methods described in this paper cannot determine a cause of the injury, but may be useful in the detection and treatment of running injuries.
608 citations
Authors
Showing all 37601 results
Name | H-index | Papers | Citations |
---|---|---|---|
George M. Whitesides | 240 | 1739 | 269833 |
Joan Massagué | 189 | 408 | 149951 |
David H. Weinberg | 183 | 700 | 171424 |
David L. Kaplan | 177 | 1944 | 146082 |
Michael I. Jordan | 176 | 1016 | 216204 |
James F. Sallis | 169 | 825 | 144836 |
Bradley T. Hyman | 169 | 765 | 136098 |
Anton M. Koekemoer | 168 | 1127 | 106796 |
Derek R. Lovley | 168 | 582 | 95315 |
Michel C. Nussenzweig | 165 | 516 | 87665 |
Alfred L. Goldberg | 156 | 474 | 88296 |
Donna Spiegelman | 152 | 804 | 85428 |
Susan E. Hankinson | 151 | 789 | 88297 |
Bernard Moss | 147 | 830 | 76991 |
Roger J. Davis | 147 | 498 | 103478 |