A nonparametric method for producing isolines of bivariate exceedance probabilities

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Related publications (30)

Tree root distribution modelling in different environmental conditions

David Andrew Barry, Paolo Perona, Massimiliano Schwarz

The ability to predict the spatial distribution of tree root system variables (e.g., the Root system Area (RA), the maximum root diameter, the number of roots in diameter classes, the density of fine roots, etc.) under different environmental conditions is ...

2022

Memory of Motion for Initializing Optimization in Robotics

Teguh Santoso Lembono

Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...

EPFL2022

Progressive Correspondence Pruning by Consensus Learning

Mathieu Salzmann, Hongwei Li, Chenxu Zhao, Feng Zhu, Rui Zhao

Correspondence pruning aims to correctly remove false matches (outliers) from an initial set of putative correspondences. The pruning process is challenging since putative matches are typically extremely unbalanced, largely dominated by outliers, and the r ...

IEEE2021

Crack propagation in CFRP laminates under mode I monotonic and fatigue loads: A methodological study

John Botsis, Charlie Joseph Simon Blondeau, Georgios Pappas

Delamination in composite materials is often accompanied by fiber bridging that increases resistance to crack growth. Here, delamination of two unidirectional carbon/epoxy systems was studied under monotonic and displacement-controlled fatigue loading. One ...

ELSEVIER SCI LTD2021

COVID-19: data-driven dynamic asset allocation in times of pandemic

Anna Timonina-Farkas

The COVID-19 pandemic has demonstrated the importance and value of multi-period asset allocation strategies responding to rapid changes in market behavior. In this article, we formulate and solve a multi-stage stochastic optimization problem, choosing the ...

AMER INST MATHEMATICAL SCIENCES-AIMS2021

Towards an in vitro cardiac model: 3D environment, co-culture, alignment, and mechanical stimulation impact on cell behavior

Fatemeh Navaee

Our aim is to develop a 3D model unit of cardiac muscle: an in-vitro analog of the trabeculae carneae found in vivo. As a base hydrogel matrix for cardiomyocyte culture in 3D, we develop a blend of decellularized extracellular matrix (dECM) and fibrin. Thi ...

EPFL2021

Worldwide performance evaluation of ground surface reflectance models

Christophe Ballif, Arttu Matias Tuomiranta, Pierre-Jean Alet

To improve the accuracy of bifacial gain estimation, recent radiative models of solar energy systems have abandoned the traditional assumption of isotropic ground-reflected radiance. However, surface reflectance itself is still commonly considered as a con ...

2021

{10(1)over-bar2} twinning mechanism during in situ micro-tensile loading of pure Mg: Role of basal slip and twin-twin interactions

Johann Michler, Amit Sharma, Daniele Casari, Roland Logé, Xavier Maeder, Nicolò Maria Della Ventura

An SEM in situ uniaxial tensile testing setup allowing HR-EBSD acquisition during deformation was used to study the extension twinning mechanism in magnesium(Mg) at the micron scale. Structures were fabricated with two different crystal orientations, respe ...

2021

Unbiased Monte Carlo cluster updates with autoregressive neural networks

Giuseppe Carleo, Dian Wu, Riccardo Rossi

Efficient sampling of complex high-dimensional probability distributions is a central task in computational science. Machine learning methods like autoregressive neural networks, used with Markov chain Monte Carlo sampling, provide good approximations to s ...

AMER PHYSICAL SOC2021

Sparsely Observed Functional Time Series: Theory and Applications

Tomas Rubin

Functional time series is a temporally ordered sequence of not necessarily independent random curves. While the statistical analysis of such data has been traditionally carried out under the assumption of completely observed functional data, it may well ha ...

EPFL2021

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