Probabilistic small data global Well-Posedness of the energy-critical Maxwell-Klein-Gordon equation

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Statistical comparison of the performance of data-based models for sewer condition modeling

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The present article proposes a methodology to consider the uncertainty intrinsic to data-based models when comparing their performance. The goal is to provide a quantification of the variability of this type of models due to the random nature of the calibr ...

2019

Learning new physics from a machine

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We propose using neural networks to detect data departures from a given reference model, with no prior bias on the nature of the new physics responsible for the discrepancy. The virtues of neural networks as unbiased function approximants make them particu ...

American Physical Society2019

Reducing Metadata Leakage from Encrypted Files and Communication with PURBs

Matthew Joshua Underwood, Jean-Pierre Hubaux, Bryan Alexander Ford, Ludovic Barman, Wouter Lueks, Kirill Nikitin

Most encrypted data formats leak metadata via their plaintext headers, such as format version, encryption schemes used, number of recipients who can decrypt the data, and even the recipients’ identities. This leakage can pose security and privacy risks to ...

Sciendo2019

Two-Tier Mapper, an unbiased topology-based clustering method for enhanced global gene expression analysis

Kathryn Hess Bellwald, Cathrin Brisken, Jacques Rougemont, Rachel Marcone

Motivation: Unbiased clustering methods are needed to analyze growing numbers of complex data sets. Currently available clustering methods often depend on parameters that are set by the user, they lack stability, and are not applicable to small data sets. ...

Oxford University Press2019

Amplitude Analysis of B-+/- -> pi(K+K-)-K-+/- Decays

Jian Wang, Mingkui Wang, Olivier Schneider, Zhirui Xu, Yiming Li, Yi Zhang, Lei Zhang, Yi Wang, Aurelio Bay, Guido Haefeli, Jessica Prisciandaro, Tatsuya Nakada, Christoph Frei, Mark Tobin, Frédéric Blanc, Greig Alan Cowan, Maurizio Martinelli, Vladislav Balagura, Donal Patrick Hill, Liang Sun, François Fleuret, Mirco Dorigo, Liupan An, Elena Graverini, Renato Quagliani, Hang Yin, Maria Vieites Diaz, Aravindhan Venkateswaran, Michel De Cian, Vladimir Macko, Federico Leo Redi, Luis Miguel Garcia Martin, Sebastian Schulte, Tommaso Colombo, Vitalii Lisovskyi, Tara Nanut, Minh Tâm Tran, Violaine Bellée, Guillaume Max Pietrzyk, Pavol Stefko, Pietro Marino, Lino Ferreira Lopes, Matthieu Philippe Luther Marinangeli, Veronica Sølund Kirsebom, Maria Elena Stramaglia, Ana Bárbara Rodrigues Cavalcante, Guido Andreassi, Luca Pescatore, Preema Rennee Pais, Maxime Schubiger, Plamen Hristov Hopchev, Chitsanu Khurewathanakul, Thi Dung Nguyen, Olivier Göran Girard, Mâu Chung Nguyên, Axel Kuonen, Vincenzo Battista, Conor Thomas Fitzpatrick, Brice Emile Maurin

The first amplitude analysis of the B-+/- -> pi(K+K-)-K-+/- decay is reported based on a data sample corresponding to an integrated luminosity of 3.0 fb(-1) of pp collisions recorded in 2011 and 2012 with the LHCb detector. The data are found to be best de ...

2019

A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms

Mikhail Kapralov, Amir Zandieh

Reconstructing continuous signals based on a small number of discrete samples is a fundamental problem across science and engineering. We are often interested in signals with "simple" Fourier structure - e.g., those involving frequencies within a bounded r ...

ASSOC COMPUTING MACHINERY2019

Deep Learning of Human Perception in Audio Event Classification

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In this paper, we introduce our recent studies on human perception in audio event classification. In particular, the pre-trained model VGGish is used as feature extractor to process audio data, and DenseNet is trained by and used as feature extractor for o ...

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Development of topological tools for the analysis of biological data

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There is a growing need for unbiased clustering algorithms, ideally automated to analyze complex data sets. Topological data analysis (TDA) has been used to approach this problem. This recent field of mathematics discerns characteristic features of a space ...

EPFL2018

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The increasing demand for extracting value out of ever-growing data poses an ongoing challenge to system designers, a task only made trickier by the end of Dennard scaling. As the performance density of traditional CPU-centric architectures stagnates, adva ...

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