Publications related to Probability interpretations

Safe Motion Planning against Multimodal Distributions Based on a Scenario Approach

We present the design of a motion planning algorithm that ensures safety for an autonomous vehicle. In particular, we consider a multimodal distribution over uncertainties; for example, the uncertain predictions of future trajectories of surrounding vehicl ...

2022

Limiting the impact of supply chain disruptions in the face of distributional uncertainty in demand

Ralf Seifert, Anna Timonina-Farkas, René Yves Glogg

Service-level requirements play a crucial role in eliminating stock-outs in a production pipeline. However, delivering a specific service level can become an unattainable goal given the various uncertainties influencing both the production pipeline and cus ...

WILEY2022

Optimal Combination Policies For Adaptive Social Learning

Ping Hu, Stefan Vlaski, Virginia Bordignon

This paper investigates the effect of combination policies on the performance of adaptive social learning in non-stationary environments. By analyzing the relation between the error probability and the underlying graph topology, we prove that in the slow a ...

IEEE2022

A General Framework for Optimal Data-Driven Optimization

Daniel Kuhn, Tobias Sutter

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...

2021

Estimation of separable direct and indirect effects in continuous time

Mats Julius Stensrud

Many research questions involve time-to-event outcomes that can be prevented from occurring due to competing events. In these settings, we must be careful about the causal interpretation of classical statistical estimands. In particular, estimands on the h ...

WILEY2021

Stochastic Optimal Control for Autonomous Driving Applications via Polynomial Chaos Expansions

Colin Neil Jones, Petr Listov, Johannes Christian Schwarz

Model-based methods in autonomous driving and advanced driving assistance gain importance in research and development due to their potential to contribute to higher road safety. Parameters of vehicle models, however, are hard to identify precisely or they ...

2021

Shrinking Scale Equidistribution for Monochromatic Random Waves on Compact Manifolds

Matthew De Courcy-Ireland

We prove equidistribution at shrinking scales for the monochromatic ensemble on a compact Riemannian manifold of any dimension. This ensemble on an arbitrary manifold takes a slowly growing spectral window in order to synthesize a random function. With hig ...

OXFORD UNIV PRESS2021

The Surface Quasi-geostrophic Equation With Random Diffusion

Klaus Martin Widmayer

Consider the surface quasi-geostrophic equation with random diffusion, white in time. We show global existence and uniqueness in high probability for the associated Cauchy problem satisfying a Gevrey type bound. This article is inspired by a recent work of ...

OXFORD UNIV PRESS2020

Robust Generalization via $\alpha$-Mutual Information

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

The aim of this work is to provide bounds connecting two probability measures of the same event using Rényi

\alpha

-Divergences and Sibson’s

\alpha

-Mutual Information, a generalization of respectively the Kullback-Leibler Divergence and Shannon’s Mutual ...

ETHZ2020

Normalized Gaussian path integrals

Giulio Corazza

Path integrals play a crucial role in describing the dynamics of physical systems subject to classical or quantum noise. In fact, when correctly normalized, they express the probability of transition between two states of the system. In this work, we show ...

AMER PHYSICAL SOC2020

Probability interpretations

Graph Chatbot

Chat with Graph Search

Safe Motion Planning against Multimodal Distributions Based on a Scenario Approach

Limiting the impact of supply chain disruptions in the face of distributional uncertainty in demand

Optimal Combination Policies For Adaptive Social Learning

A General Framework for Optimal Data-Driven Optimization

Estimation of separable direct and indirect effects in continuous time

Stochastic Optimal Control for Autonomous Driving Applications via Polynomial Chaos Expansions

Shrinking Scale Equidistribution for Monochromatic Random Waves on Compact Manifolds

The Surface Quasi-geostrophic Equation With Random Diffusion

Robust Generalization via $\alpha$-Mutual Information

Normalized Gaussian path integrals

Optimal Combination Policies For Adaptive Social Learning

Safe Motion Planning against Multimodal Distributions Based on a Scenario Approach

Limiting the impact of supply chain disruptions in the face of distributional uncertainty in demand

A General Framework for Optimal Data-Driven Optimization

Shrinking Scale Equidistribution for Monochromatic Random Waves on Compact Manifolds

Normalized Gaussian path integrals

The Surface Quasi-geostrophic Equation With Random Diffusion

Robust Generalization via $\alpha$-Mutual Information

Estimation of separable direct and indirect effects in continuous time

Stochastic Optimal Control for Autonomous Driving Applications via Polynomial Chaos Expansions