Publications related to Creating Probabilistic Databases from Imprecise Time-Series Data

On distributional autoregression and iterated transportation

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

Hoboken2024

On Approximations of Data-Driven Chance Constrained Programs over Wasserstein Balls

Daniel Kuhn, Zhi Chen, Wolfram Wiesemann

Distributionally robust chance constrained programs minimize a deterministic cost function subject to the satisfaction of one or more safety conditions with high probability, given that the probability distribution of the uncertain problem parameters affec ...

2022

A birth-death-migration model for life in astrophysical environments

Claudio Grimaldi

To assess the number of life-bearing worlds in astrophysical environments, it is necessary to take the intertwined processes of abiogenesis (birth), extinction (death), and transfer of life (migration) into account. We construct a mathematical model that i ...

OXFORD UNIV PRESS2021

Towards Interactions Through Differentiable-Non-Differentiable Scale Transitions In Scale Relativity Theory

Maria-Alexandra Paun

It is shown that, in the framework of Scale Relativity Theory, correlations of type informational entropy/cross entropy - probability density, in the description of the dynamics of any complex system, can be perceived as interactions. Explaining these inte ...

UNIV POLITEHNICA BUCHAREST, SCI BULL2021

Simulation-based Anomaly Detection and Damage Localization: An application to Structural Health Monitoring

Jan Sickmann Hesthaven, Caterina Bigoni

We propose a simulation-based decision strategy for the proactive maintenance of complex structures with a particular application to structural health monitoring (SHM). The strategy is based on a data-driven approach which exploits an offline-online decomp ...

2020

Statistical Aspects of Wasserstein Distances

Victor Panaretos, Yoav Zemel

Wasserstein distances are metrics on probability distributions inspired by the problem of optimal mass transportation. Roughly speaking, they measure the minimal effort required to reconfigure the probability mass of one distribution in order to recover th ...

ANNUAL REVIEWS2019

MATHICSE Technical Report: Simulation-Based Anomaly Detection and Damage Localization: an Application to Structural Health Monitoring

Jan Sickmann Hesthaven, Caterina Bigoni

We propose a simulation-based decision strategy for the proactive maintenance of complex structures with a particular application to structural health monitoring (SHM). The strategy is based on a data-driven approach which exploits an offine-online decompo ...

MATHICSE2019

Extracting the Critical Rooting Length in Plant Uprooting by Flow From Pullout Experiments

Paolo Perona, Giulio Calvani

The growth and establishment of riparian vegetation on river bedforms is of hydrological as well as ecological importance as it helps in enhancing spatial heterogeneity and thus the biodiversity of river corridors. Yet, during floods, flow drag and scourin ...

AGU2019

Efficient learning of smooth probability functions from Bernoulli tests with guarantees.

Volkan Cevher, Paul Thierry Yves Rolland, Ali Kavis

We study the fundamental problem of learning an unknown, smooth probability function via pointwise Bernoulli tests. We provide a scalable algorithm for efficiently solving this problem with rigorous guarantees. In particular, we prove the convergence rate ...

2019

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Fei Pu

In this thesis, we study systems of linear and/or non-linear stochastic heat equations and fractional heat equations in spatial dimension

1

driven by space-time white noise. The main topic is the study of hitting probabilities for the solutions to these ...

EPFL2018

Creating Probabilistic Databases from Imprecise Time-Series Data

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On distributional autoregression and iterated transportation

On Approximations of Data-Driven Chance Constrained Programs over Wasserstein Balls

A birth-death-migration model for life in astrophysical environments

Towards Interactions Through Differentiable-Non-Differentiable Scale Transitions In Scale Relativity Theory

Simulation-based Anomaly Detection and Damage Localization: An application to Structural Health Monitoring

Statistical Aspects of Wasserstein Distances

MATHICSE Technical Report: Simulation-Based Anomaly Detection and Damage Localization: an Application to Structural Health Monitoring

Extracting the Critical Rooting Length in Plant Uprooting by Flow From Pullout Experiments

Efficient learning of smooth probability functions from Bernoulli tests with guarantees.

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

On distributional autoregression and iterated transportation

Towards Interactions Through Differentiable-Non-Differentiable Scale Transitions In Scale Relativity Theory

Statistical Aspects of Wasserstein Distances

A birth-death-migration model for life in astrophysical environments

On Approximations of Data-Driven Chance Constrained Programs over Wasserstein Balls

Simulation-based Anomaly Detection and Damage Localization: An application to Structural Health Monitoring

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

MATHICSE Technical Report: Simulation-Based Anomaly Detection and Damage Localization: an Application to Structural Health Monitoring

Efficient learning of smooth probability functions from Bernoulli tests with guarantees.

Extracting the Critical Rooting Length in Plant Uprooting by Flow From Pullout Experiments