Institution
ETH Zurich
Education•Zurich, Switzerland•
About: ETH Zurich is a education organization based out in Zurich, Switzerland. It is known for research contribution in the topics: Population & Computer science. The organization has 48393 authors who have published 122408 publications receiving 5111383 citations. The organization is also known as: Swiss Federal Institute of Technology in Zurich & Eidgenössische Technische Hochschule Zürich.
Topics: Population, Computer science, Catalysis, Context (language use), Laser
Papers published on a yearly basis
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TL;DR: In this article, the first derivative of an estimator viewed as functional and the ways in which it can be used to study local robustness properties are discussed, and a theory of robust estimation "near" strict parametric models is briefly sketched and applied to some classical situations.
Abstract: This paper treats essentially the first derivative of an estimator viewed as functional and the ways in which it can be used to study local robustness properties. A theory of robust estimation “near” strict parametric models is briefly sketched and applied to some classical situations. Relations between von Mises functionals, the jackknife and U-statistics are indicated. A number of classical and new estimators are discussed, including trimmed and Winsorized means, Huber-estimators, and more generally maximum likelihood and M-estimators. Finally, a table with some numerical robustness properties is given.
2,410 citations
27 Sep 1998
TL;DR: In this paper an extensive, quantitative comparison is presented, applying four multiobjective evolutionary algorithms to an extended 0/1 knapsack problem.
Abstract: Since 1985 various evolutionary approaches to multiobjective optimization have been developed, capable of searching for multiple solutions concurrently in a single run. But the few comparative studies of different methods available to date are mostly qualitative and restricted to two approaches. In this paper an extensive, quantitative comparison is presented, applying four multiobjective evolutionary algorithms to an extended 0/1 knapsack problem.
2,401 citations
21 Jul 2017
TL;DR: It is concluded that the NTIRE 2017 challenge pushes the state-of-the-art in single-image super-resolution, reaching the best results to date on the popular Set5, Set14, B100, Urban100 datasets and on the authors' newly proposed DIV2K.
Abstract: This paper introduces a novel large dataset for example-based single image super-resolution and studies the state-of-the-art as emerged from the NTIRE 2017 challenge. The challenge is the first challenge of its kind, with 6 competitions, hundreds of participants and tens of proposed solutions. Our newly collected DIVerse 2K resolution image dataset (DIV2K) was employed by the challenge. In our study we compare the solutions from the challenge to a set of representative methods from the literature and evaluate them using diverse measures on our proposed DIV2K dataset. Moreover, we conduct a number of experiments and draw conclusions on several topics of interest. We conclude that the NTIRE 2017 challenge pushes the state-of-the-art in single-image super-resolution, reaching the best results to date on the popular Set5, Set14, B100, Urban100 datasets and on our newly proposed DIV2K.
2,388 citations
TL;DR: In this article, a new finite element method is presented that features the ability to include in the finite element space knowledge about the partial differential equation being solved, which can therefore be more efficient than the usual finite element methods.
Abstract: A new finite element method is presented that features the ability to include in the finite element space knowledge about the partial differential equation being solved This new method can therefore be more efficient than the usual finite element methods An additional feature of the partition-of-unity method is that finite element spaces of any desired regularity can be constructed very easily This paper includes a convergence proof of this method and illustrates its efficiency by an application to the Helmholtz equation for high wave numbers The basic estimates for a posteriori error estimation for this new method are also proved © 1997 by John Wiley & Sons, Ltd
2,387 citations
University of California, San Diego1, University of Montana2, Stanford University3, Scripps Institution of Oceanography4, National Autonomous University of Mexico5, Salk Institute for Biological Studies6, San Diego State University7, Strathclyde Institute of Pharmacy and Biomedical Sciences8, Lawrence Berkeley National Laboratory9, Harvard University10, University of Rennes11, University of Minnesota12, University of Lorraine13, Technical University of Denmark14, University of California, Los Angeles15, J. Craig Venter Institute16, University of Washington17, ETH Zurich18, University of Illinois at Chicago19, National Sun Yat-sen University20, Academia Sinica21, University of Münster22, Victoria University of Wellington23, University of North Carolina at Chapel Hill24, Indiana University25, Smithsonian Tropical Research Institute26, University of São Paulo27, Federal University of Mato Grosso do Sul28, University of Notre Dame29, University of California, Santa Cruz30, Oregon State University31, University of California, Berkeley32, Florida International University33, University of Hawaii at Manoa34, University of Geneva35, Institut de Chimie des Substances Naturelles36, Pacific Northwest National Laboratory37, National Institutes of Health38, Chinese Academy of Sciences39
TL;DR: In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations and data-driven social-networking should facilitate identification of spectra and foster collaborations.
Abstract: The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.
2,365 citations
Authors
Showing all 49062 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Ralph Weissleder | 184 | 1160 | 142508 |
| Ruedi Aebersold | 182 | 879 | 141881 |
| David L. Kaplan | 177 | 1944 | 146082 |
| Andrea Bocci | 172 | 2402 | 176461 |
| Richard H. Friend | 169 | 1182 | 140032 |
| Lorenzo Bianchini | 152 | 1516 | 106970 |
| David D'Enterria | 150 | 1592 | 116210 |
| Andreas Pfeiffer | 149 | 1756 | 131080 |
| Bernhard Schölkopf | 148 | 1092 | 149492 |
| Martin J. Blaser | 147 | 820 | 104104 |
| Sebastian Thrun | 146 | 434 | 98124 |
| Antonio Lanzavecchia | 145 | 408 | 100065 |
| Christoph Grab | 144 | 1359 | 144174 |
| Kurt Wüthrich | 143 | 739 | 103253 |
| Maurizio Pierini | 143 | 1782 | 104406 |