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A Hybrid Approach Between Adversarial Generative Networks and Actor-Critic Policy Gradient for Low Rate High-Resolution Image CompressionJun 11 2019Image compression is an essential approach for decreasing the size in bytes of the image without deteriorating the quality of it. Typically, classic algorithms are used but recently deep-learning has been successfully applied. In this work, is presented ... More

V-FCNN: Volumetric Fully Convolution Neural Network For Automatic Atrial SegmentationAug 06 2018Sep 27 2018Atrial Fibrillation (AF) is a common electro-physiological cardiac disorder that causes changes in the anatomy of the atria. A better characterization of these changes is desirable for the definition of clinical biomarkers, furthermore, thus there is ... More

A Generative Adversarial Model for Right Ventricle SegmentationSep 27 2018The clinical management of several cardiovascular conditions, such as pulmonary hypertension, require the assessment of the right ventricular (RV) function. This work addresses the fully automatic and robust access to one of the key RV biomarkers, its ... More

Automated segmentation on the entire cardiac cycle using a deep learning work-flowAug 31 2018The segmentation of the left ventricle (LV) from CINE MRI images is essential to infer important clinical parameters. Typically, machine learning algorithms for automated LV segmentation use annotated contours from only two cardiac phases, diastole, and ... More

On the adiabatic limit of Hadamard statesSep 10 2016We consider the adiabatic limit of Hadamard states for free quantum Klein-Gordon fields, when the background metric and the field mass are slowly varied from their initial to final values. If the Klein-Gordon field stays massive, we prove that the adiabatic ... More

On the adiabatic limit of Hadamard statesSep 10 2016Feb 07 2017We consider the adiabatic limit of Hadamard states for free quantum Klein-Gordon fields, when the background metric and the field mass are slowly varied from their initial to final values. If the Klein-Gordon field stays massive, we prove that the adiabatic ... More

Long-distance quantum key distribution with imperfect devicesOct 30 2012Apr 08 2013Quantum key distribution over probabilistic quantum repeaters is addressed. We compare, under practical assumptions, two such schemes in terms of their secure key generation rates per quantum memory. The two schemes under investigation are the one proposed ... More

Long-Distance Trust-Free Quantum Key DistributionJul 30 2014Nov 25 2014The feasibility of trust-free long-haul quantum key distribution (QKD) networks is addressed. We combine measurement-device-independent QKD (MDI-QKD), as an access technology, with a quantum repeater setup, at the core of future quantum communication ... More

Valuation of contingent convertible catastrophe bonds - the case for equity conversionApr 21 2018Within the context of the banking-related literature on contingent convertible bonds, we comprehensively formalise the design and features of a relatively new type of insurance-linked security, called a contingent convertible catastrophe bond (CocoCat). ... More

Measurement-device-independent quantum key distribution with ensemble-based memoriesJul 30 2014Nov 25 2014Quantum memories are enabling devices for extending the reach of quantum key distribution (QKD) systems. The required specifications for memories are, however, often considered too demanding for available technologies. One can change this mindset by introducing ... More

Ribbon Graphs and Mirror Symmetry IMar 12 2011Given a ribbon graph $\Gamma$ with some extra structure, we define, using constructible sheaves, a dg category $CPM(\Gamma)$ meant to model the Fukaya category of a Riemann surface in the cell of Teichm\"uller space described by $\Gamma.$ When $\Gamma$ ... More

What does past correlation structure tell us about the future? An answer from network filteringMay 28 2016We discovered that past changes in the market correlation structure are significantly related with future changes in the market volatility. By using correlation-based information filtering networks we device a new tool for forecasting the market volatility ... More

Risk diversification: a study of persistence with a filtered correlation-network approachOct 21 2014The evolution with time of the correlation structure of equity returns is studied by means of a filtered network approach investigating persistences and recurrences and their implications for risk diversification strategies. We build dynamically Planar ... More

Measurement-device-independent quantum key distribution with nitrogen vacancy centers in diamondMar 11 2016Mar 29 2017Memory-assisted measurement-device-independent quantum key distribution (MA-MDI-QKD) has recently been proposed as a possible intermediate step towards the realization of quantum repeaters. Despite its relaxing some of the requirements on quantum memories, ... More

Bootstrapping topology and systemic risk of complex network using the fitness modelSep 28 2012We present a novel method to reconstruct complex network from partial information. We assume to know the links only for a subset of the nodes and to know some non-topological quantity (fitness) characterising every node. The missing links are generated ... More

Low Complexity Indoor Localization in Wireless Sensor Networks by UWB and Inertial Data FusionMay 07 2013Precise indoor localization of moving targets is a challenging activity which cannot be easily accomplished without combining different sources of information. In this sense, the combination of different data sources with an appropriate filter might improve ... More

Measurement-device-independent quantum key distribution with nitrogen vacancy centers in diamondMar 11 2016Sep 29 2016Memory-assisted measurement-device-independent quantum key distribution (MA-MDI-QKD) has recently been proposed as a possible intermediate step towards the realization of quantum repeaters. Despite its relaxing some of the requirements on quantum memories, ... More

Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with UltrasoundJul 11 2018The automatic analysis of ultrasound sequences can substantially improve the efficiency of clinical diagnosis. In this work we present our attempt to automate the challenging task of measuring the vascular diameter of the fetal abdominal aorta from ultrasound ... More

Fault-Trajectory Approach for Fault Diagnosis on Analog CircuitsOct 25 2007This issue discusses the fault-trajectory approach suitability for fault diagnosis on analog networks. Recent works have shown promising results concerning a method based on this concept for ATPG for diagnosing faults on analog networks. Such method relies ... More

Phase estimation via quantum interferometry for noisy detectorsJul 19 2011Oct 12 2012The sensitivity in optical interferometry is strongly affected by losses during the signal propagation or at the detection stage. The optimal quantum states of the probing signals in the presence of loss were recently found. However, in many cases of ... More

The multiplex dependency structure of financial marketsJun 15 2016We propose here a multiplex network approach to investigate simultaneously different types of dependency in complex data sets. In particular, we consider multiplex networks made of four layers corresponding respectively to linear, non-linear, tail, and ... More

Liquid-Liquid Phase Separation in an Elastic NetworkSep 01 2017Sep 27 2017Living and engineered systems rely on the stable coexistence of two interspersed liquid phases. Yet surface tension drives their complete separation. Here we show that stable droplets of uniform and tuneable size can be produced through arrested phase ... More

Network-based indicators of Bitcoin bubblesMay 11 2018The functioning of the cryptocurrency Bitcoin relies on the open availability of the entire history of its transactions. This makes it a particularly interesting socio-economic system to analyse from the point of view of network science. Here we analyse ... More

Observation of Majorization Principle for quantum algorithms via 3-D integrated photonic circuitsAug 03 2016The Majorization Principle is a fundamental statement governing the dynamics of information processing in optimal and efficient quantum algorithms. While quantum computation can be modeled to be reversible, due to the unitary evolution undergone by the ... More

The design of the MEG II experimentJan 15 2018The MEG experiment, designed to search for the mu+->e+ gamma decay at a 10^-13 sensitivity level, completed data taking in 2013. In order to increase the sensitivity reach of the experiment by an order of magnitude to the level of 6 x 10-14 for the branching ... More