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The efficiency of stochastic particle schemes for large scale simulations relies on the ability to preserve a uniform distribution of particles in the whole physical domain. While simple particle split and merge algorithms have been considered previously, ...
In our recent work, the sampling and reconstruction of non-decaying signals, modeled as members of weighted-L-p spaces, were shown to be stable with an appropriate choice of the generating kernel for the shift-invariant reconstruction space. In this paper, ...
A directed acyclic graph (DAG) is the most common graphical model for representing causal relationships among a set of variables. When restricted to using only observational data, the structure of the ground truth DAG is identifiable only up to Markov equi ...
We show how an event topology classification based on deep learning could be used to improve the purity of data samples selected in real-time at the Large Hadron Collider. We consider different data representations, on which different kinds of multi-class ...
Exploration methods combine parametric energy assessments and data visualization to support building designers at early design stages. When exploration methods come to Life-Cycle Assessment (LCA) and the Global Warming Potential (GWP) assessment, a larger ...
Is it possible to design a packet-sampling algorithm that prevents the network node that performs the sampling from treating the sampled packets preferentially? We study this problem in the context of designing a "network transparency" system. In this syst ...
In the last decade, Compressive Sensing (CS) has emerged as the most promising, model-driven approach to accelerate MRI scans. CS relies on the key sparsity assumption and proposes random sampling for data acquisition. The practical CS approaches in MRI em ...
Sparse recovery from undersampled random quan- tization measurements is a recent active research topic. Previous work asserts that stable recovery can be guaranteed via the basis pursuit dequantizer (BPDQ) if the measurements number is large enough, consid ...
Wearable sweat sensing systems offer non-invasive and real-time bio-data streaming solutions. They open the possibility for continuous monitoring of biomarkers' concentrations as well as their variation in sweat, which is a complementary to current passive ...
A key feature of resorcin[4]arene cavitands is their ability to switch between a closed/contracted (Vase) and an open/expanded (Kite) conformation. The mechanism and dynamics of this interconversion remains, however, elusive. In the present study, the Vase ...
