Institution
École Polytechnique
Education•Palaiseau, France•
About: École Polytechnique is a education organization based out in Palaiseau, France. It is known for research contribution in the topics: Laser & Plasma. The organization has 18995 authors who have published 39265 publications receiving 1225163 citations. The organization is also known as: Ecole Polytechnique & Polytechnique.
Topics: Laser, Plasma, Population, Electron, Femtosecond
Papers published on a yearly basis
Papers
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University of Udine1, University of Lugano2, École Polytechnique Fédérale de Lausanne3, Leipzig University4, University of Paris5, University of North Texas6, Princeton University7, National Research Council8, International School for Advanced Studies9, Cornell University10, University of Lincoln11, University of Milan12, École Polytechnique13, International Centre for Theoretical Physics14, University of Paderborn15, University of Oxford16, Jožef Stefan Institute17, University of Padua18, Sapienza University of Rome19, Vietnam Academy of Science and Technology20, University of British Columbia21, Centre national de la recherche scientifique22, University of Lorraine23, University of Zurich24, École Normale Supérieure25, Université Paris-Saclay26, Wake Forest University27, Temple University28
TL;DR: Quantum ESPRESSO as discussed by the authors is an integrated suite of open-source computer codes for quantum simulations of materials using state-of-the-art electronic-structure techniques, based on density functional theory, density functional perturbation theory, and many-body perturbations theory, within the plane-wave pseudo-potential and projector-augmented-wave approaches.
Abstract: Quantum ESPRESSO is an integrated suite of open-source computer codes for quantum simulations of materials using state-of-the art electronic-structure techniques, based on density-functional theory, density-functional perturbation theory, and many-body perturbation theory, within the plane-wave pseudo-potential and projector-augmented-wave approaches. Quantum ESPRESSO owes its popularity to the wide variety of properties and processes it allows to simulate, to its performance on an increasingly broad array of hardware architectures, and to a community of researchers that rely on its capabilities as a core open-source development platform to implement theirs ideas. In this paper we describe recent extensions and improvements, covering new methodologies and property calculators, improved parallelization, code modularization, and extended interoperability both within the distribution and with external software.
2,818 citations
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01 Jan 2015TL;DR: This paper extends the idea of a student network that could imitate the soft output of a larger teacher network or ensemble of networks, using not only the outputs but also the intermediate representations learned by the teacher as hints to improve the training process and final performance of the student.
Abstract: While depth tends to improve network performances, it also makes gradient-based training more difficult since deeper networks tend to be more non-linear. The recently proposed knowledge distillation approach is aimed at obtaining small and fast-to-execute models, and it has shown that a student network could imitate the soft output of a larger teacher network or ensemble of networks. In this paper, we extend this idea to allow the training of a student that is deeper and thinner than the teacher, using not only the outputs but also the intermediate representations learned by the teacher as hints to improve the training process and final performance of the student. Because the student intermediate hidden layer will generally be smaller than the teacher's intermediate hidden layer, additional parameters are introduced to map the student hidden layer to the prediction of the teacher hidden layer. This allows one to train deeper students that can generalize better or run faster, a trade-off that is controlled by the chosen student capacity. For example, on CIFAR-10, a deep student network with almost 10.4 times less parameters outperforms a larger, state-of-the-art teacher network.
2,560 citations
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TL;DR: Knowing how organisms retain the ability to regenerate tissue throughout adult life might help to unlock latent regenerative pathways in humans, which would change medical practice as much as the introduction of antibiotics did in the twentieth century.
Abstract: The repair of wounds is one of the most complex biological processes that occur during human life. After an injury, multiple biological pathways immediately become activated and are synchronized to respond. In human adults, the wound repair process commonly leads to a non-functioning mass of fibrotic tissue known as a scar. By contrast, early in gestation, injured fetal tissues can be completely recreated, without fibrosis, in a process resembling regeneration. Some organisms, however, retain the ability to regenerate tissue throughout adult life. Knowledge gained from studying such organisms might help to unlock latent regenerative pathways in humans, which would change medical practice as much as the introduction of antibiotics did in the twentieth century.
2,513 citations
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TL;DR: Tunnels based on ultrathin semiconducting films or nanowires could achieve a 100-fold power reduction over complementary metal–oxide–semiconductor transistors, so integrating tunnel FETs with CMOS technology could improve low-power integrated circuits.
Abstract: Power dissipation is a fundamental problem for nanoelectronic circuits. Scaling the supply voltage reduces the energy needed for switching, but the field-effect transistors (FETs) in today's integrated circuits require at least 60 mV of gate voltage to increase the current by one order of magnitude at room temperature. Tunnel FETs avoid this limit by using quantum-mechanical band-to-band tunnelling, rather than thermal injection, to inject charge carriers into the device channel. Tunnel FETs based on ultrathin semiconducting films or nanowires could achieve a 100-fold power reduction over complementary metal-oxide-semiconductor (CMOS) transistors, so integrating tunnel FETs with CMOS technology could improve low-power integrated circuits.
2,390 citations
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TL;DR: The problem of automatically tuning multiple parameters for pattern recognition Support Vector Machines (SVMs) is considered by minimizing some estimates of the generalization error of SVMs using a gradient descent algorithm over the set of parameters.
Abstract: The problem of automatically tuning multiple parameters for pattern recognition Support Vector Machines (SVMs) is considered. This is done by minimizing some estimates of the generalization error of SVMs using a gradient descent algorithm over the set of parameters. Usual methods for choosing parameters, based on exhaustive search become intractable as soon as the number of parameters exceeds two. Some experimental results assess the feasibility of our approach for a large number of parameters (more than 100) and demonstrate an improvement of generalization performance.
2,323 citations
Authors
Showing all 19056 results
Name | H-index | Papers | Citations |
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Michael Grätzel | 248 | 1423 | 303599 |
Jing Wang | 184 | 4046 | 202769 |
David L. Kaplan | 177 | 1944 | 146082 |
Lorenzo Bianchini | 152 | 1516 | 106970 |
David D'Enterria | 150 | 1592 | 116210 |
Vivek Sharma | 150 | 3030 | 136228 |
Melody A. Swartz | 148 | 1304 | 103753 |
Edward G. Lakatta | 146 | 858 | 88637 |
Carlo Rovelli | 146 | 1502 | 103550 |
Marc Besancon | 143 | 1799 | 106869 |
Maksym Titov | 139 | 1573 | 128335 |
Jean-Paul Kneib | 138 | 805 | 89287 |
Yves Sirois | 137 | 1334 | 95714 |
Maria Spiropulu | 135 | 1455 | 96674 |
Shaik M. Zakeeruddin | 133 | 453 | 76010 |