Fusing Loop Detector and Probe Vehicle Data to Estimate Travel Time Statistics on Signalized Urban Networks

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As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

Atomistic simulations performed with a family of model potential with tunable hardness have proven to be a great tool for advancing the understanding of wear processes at the asperity level. They have been instrumental in finding a critical length scale, w ...

We use generalized Ray-Knight theorems, introduced by B. Toth in 1996, together with techniques developed for excited random walks as main tools for establishing positive and negative results concerning convergence of some classes of diffusively scaled sel ...

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

Interactions are ubiquitous in our world, spanning from social interactions between human individuals to physical interactions between robots and objects to mechanistic interactions among different components of an intelligent system. Despite their prevale ...

Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale ...

The HST treasury programme BUFFALO provides extended wide-field imaging of the six Hubble Frontier Fields galaxy clusters. Here we present the combined strong and weak-lensing analysis of Abell 370, a massive cluster at z = 0.375. From the reconstructed to ...

This article presents the Lightning Performance (LP) assessment of a realistic portion of the Italian distribution network with the use of probability distributions for lightning parameters inferred from local data recorded by a Lightning Location System ( ...

In this thesis, we investigate the inverse problem of trees and barcodes from a combinatorial, geometric, probabilistic and statistical point of view. Computing the persistent homology of a merge tree yields a barcode B. Reconstructing a tree from B invol ...

In this article an approximated version of the multi-species, non-linear Coulomb collision operator is derived via the use of a truncated moment expansion of the distribution function to compute the Rosenbluth potentials. The evolution of the distribution ...

The early time high altitude electromagnetic pulse conducted environment calculation is revisited by using the transmission line (TL) theory and including high-frequency corrections that were not present in the earlier studies. Waveform salient parameters, ...

The present invention describes an imaging system that allows visualization of a wide range of samples both in terms of morphology and in terms of material (e.g. density distribution, varying chemical composition, or anything that induces a change of optic ...

In multiple testing problems where the components come from a mixture model of noise and true effect, we seek to first test for the existence of the non-zero components, and then identify the true alternatives under a fixed significance level

\alpha

. Two ...

We consider a setup in which confidential i.i.d. samples X1, . . . , Xn from an unknown finite-support distribution p are passed through n copies of a discrete privatization chan- nel (a.k.a. mechanism) producing outputs Y1, . . . , Yn. The channel law gua ...

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 ...

Given a sequence L & x2d9;epsilon of Levy noises, we derive necessary and sufficient conditions in terms of their variances sigma 2(epsilon) such that the solution to the stochastic heat equation with noise sigma(epsilon)-1L & x2d9;epsilon converges in law ...

The classical multivariate extreme-value theory concerns the modeling of extremes in a multivariate random sample, suggesting the use of max-stable distributions. In this work, the classical theory is extended to the case where aggregated data, such as max ...

Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...

%0 Conference Paper %T Bayesian Differential Privacy for Machine Learning %A Aleksei Triastcyn %A Boi Faltings %B Proceedings of the 37th International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2020 %E Hal Daumé III %E A ...

We present a non-perturbative calculation of the 1-point probability distribution function (PDF) for the spherically-averaged matter density field. The PDF is represented as a path integral and is evaluated using the saddle-point method. It factorizes into ...

Fusing Loop Detector and Probe Vehicle Data to Estimate Travel Time Statistics on Signalized Urban Networks

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Extensions of Peer Prediction Incentive Mechanisms

A story of two transitions: From adhesive to abrasive wear and from ductile to brittle regime

CONVERGENCE AND NONCONVERGENCE OF SCALED SELF-INTERACTING RANDOM WALKS TO BROWNIAN MOTION PERTURBED AT EXTREMA

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics

Beyond the ultradeep frontier fields and legacy observations (BUFFALO): a high-resolution strong plus weak-lensing view of Abell 370

Assessment of the Lightning Performance of overhead distribution lines based on Lightning Location Systems data

From Trees to Barcodes and Back Again: A Combinatorial, Probabilistic and Geometric Study of a Topological Inverse Problem

Moment approach of the multi-species non-linear Coulomb collision operator adapted to particle-in-cell codes

Revisiting the Calculation of the Early Time HEMP Conducted Environment

System and methods for differential imaging using a lock-in camera

Multiple testing with test statistics following heavy-tailed distributions

Locally Differentially-Private Randomized Response for Discrete Distribution Learning

Unbiased Monte Carlo cluster updates with autoregressive neural networks

Normal approximation of the solution to the stochastic heat equation with Levy noise

Multivariate extremes over a random number of observations

Wasserstein Distributionally Robust Learning

Bayesian Differential Privacy for Machine Learning

Non-perturbative probability distribution function for cosmological counts in cells