Institution
Pompeu Fabra University
Education•Barcelona, Spain•
About: Pompeu Fabra University is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Population & Gene. The organization has 8093 authors who have published 23570 publications receiving 858431 citations. The organization is also known as: Universitat Pompeu Fabra & UPF.
Topics: Population, Gene, European union, Genome, Context (language use)
Papers published on a yearly basis
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TL;DR: This work identifies the proteins most vulnerable to aggregation as those whose cellular concentrations are high relative to their solubilities and finds that these supersaturated proteins represent a metastable subproteome involved in pathological aggregation during stress and aging and are overrepresented in biochemical processes associated with neurodegenerative disorders.
240 citations
TL;DR: The findings confirm the hypothesis that more time spent in green space is associated with higher scores on mental health and vitality scales, independent of cultural and climatic contexts.
240 citations
TL;DR: It is suggested that NFAT5 participates in specific aspects of host defense by upregulating TNF family genes and other target genes in T cells by regulating expression of the TNFα and lymphotoxin-β genes in osmotically stressed T cells.
240 citations
20 Apr 2009
TL;DR: Based on a performance evaluation, the outcome of the methods for visual diversification of image search results closely resembles human perception of diversity, which was established in an extensive clustering experiment carried out by human assessors.
Abstract: Due to the reliance on the textual information associated with an image, image search engines on the Web lack the discriminative power to deliver visually diverse search results. The textual descriptions are key to retrieve relevant results for a given user query, but at the same time provide little information about the rich image content.In this paper we investigate three methods for visual diversification of image search results. The methods deploy lightweight clustering techniques in combination with a dynamic weighting function of the visual features, to best capture the discriminative aspects of the resulting set of images that is retrieved. A representative image is selected from each cluster, which together form a diverse result set.Based on a performance evaluation we find that the outcome of the methods closely resembles human perception of diversity, which was established in an extensive clustering experiment carried out by human assessors.
240 citations
04 Aug 2015
TL;DR: This article used a transition-based parser that uses LSTM to learn representations of the parser state, replacing lookup-based word representations with representations constructed from the orthographic representation of the words, also using LSTMs.
Abstract: We present extensions to a continuousstate dependency parsing method that makes it applicable to morphologically rich languages. Starting with a highperformance transition-based parser that uses long short-term memory (LSTM) recurrent neural networks to learn representations of the parser state, we replace lookup-based word representations with representations constructed from the orthographic representations of the words, also using LSTMs. This allows statistical sharing across word forms that are similar on the surface. Experiments for morphologically rich languages show that the parsing model benefits from incorporating the character-based encodings of words.
239 citations
Authors
Showing all 8248 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Andrei Shleifer | 171 | 514 | 271880 |
| Paul Elliott | 153 | 773 | 103839 |
| Bert Brunekreef | 124 | 806 | 81938 |
| Philippe Aghion | 122 | 507 | 73438 |
| Anjana Rao | 118 | 337 | 61395 |
| Jordi Sunyer | 115 | 798 | 57211 |
| Kenneth J. Arrow | 113 | 411 | 111221 |
| Xavier Estivill | 110 | 673 | 59568 |
| Roderic Guigó | 108 | 304 | 106914 |
| Mark J. Nieuwenhuijsen | 107 | 647 | 49080 |
| Jordi Alonso | 107 | 523 | 64058 |
| Alfonso Valencia | 106 | 542 | 55192 |
| Luis Serrano | 105 | 452 | 42515 |
| Vadim N. Gladyshev | 102 | 490 | 34148 |
| Josep M. Antó | 100 | 493 | 38663 |