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The optimization of fuel-optimal low-thrust collision avoidance maneuvers (CAMs) in scenarios involving multiple encounters between spacecraft is addressed. The optimization's objective is the minimization of the total fuel consumption…

Optimization and Control · Mathematics 2024-06-07 Zeno Pavanello , Laura Pirovano , Roberto Armellin , Andrea De Vittori , Pierluigi Di Lizia

The logistic specification has been used extensively in non-Bayesian statistics to model the dependence of discrete outcomes on the values of specified covariates. Because the likelihood function is globally weakly concave estimation by…

Computation · Statistics 2013-04-17 John Geweke , Garland Durham , Huaxin Xu

Moment-based estimation filters have successfully aided spacecraft navigation for decades. However, future missions plan to venture into deep-space regimes with significant round-trip light-time telecommunication delays, operate in…

Earth and Planetary Astrophysics · Physics 2025-08-13 Benjamin L. Hanson , Todd A. Ely , Thomas R. Bewley , Aaron J. Rosengren

In this paper we are concerned with the simulation of crowds in built environments, where obstacles play a role in the dynamics and in the interactions among pedestrians. First of all, we review the state-of-the-art of the techniques for…

Optimization and Control · Mathematics 2017-01-16 Emiliano Cristiani , Daniele Peri

Simulation is a powerful tool to better understand physical systems, but generally requires computationally expensive numerical methods. Downstream applications of such simulations can become computationally infeasible if they require many…

Machine Learning · Computer Science 2024-07-17 Yoeri Poels , Koen Minartz , Harshit Bansal , Vlado Menkovski

This paper, which is Part 1 of a two-part paper series, considers a simulation-based inference with learned summary statistics, in which such a learned summary statistic serves as an empirical-likelihood with ameliorative effects in the…

Machine Learning · Statistics 2026-02-02 Getachew K. Befekadu

Physics simulation is paramount for modeling and utilizing 3D scenes in various real-world applications. However, integrating with state-of-the-art 3D scene rendering techniques such as Gaussian Splatting (GS) remains challenging. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Piotr Borycki , Weronika Smolak , Joanna Waczyńska , Marcin Mazur , Sławomir Tadeja , Przemysław Spurek

It is often desirable to build a statistical emulator of a complex computer simulator in order to perform analysis which would otherwise be computationally infeasible. We propose methodology to model multivariate output from a computer…

Methodology · Statistics 2017-01-03 Veronica E. Bowman , David C. Woods

The increase in complexity of autonomous systems is accompanied by a need of data-driven development and validation strategies. Advances in computer graphics and cloud clusters have opened the way to massive parallel high fidelity…

Machine Learning · Computer Science 2023-01-05 Osama Maqbool , Jürgen Roßmann

Storm surge, the onshore rush of sea water caused by the high winds and low pressure associated with a hurricane, can compound the effects of inland flooding caused by rainfall, leading to loss of property and loss of life for residents of…

Applications · Statistics 2009-09-29 Brian J. Reich , Montserrat Fuentes

In any spacecraft landing mission, fuel-efficient precision soft landing while avoiding nearby hazardous terrain is of utmost importance. Very few existing literature have attempted addressing both the problems of precision soft landing and…

Systems and Control · Electrical Eng. & Systems 2025-02-03 Sheikh Zeeshan Basar , Satadal Ghosh

Geostatistical modeling of the reservoir intrinsic properties starts only with sparse data available. These estimates will depend largely on the number of wells and their location. The drilling costs are so high that they do not allow new…

Applications · Statistics 2017-02-16 Júlio Caineta

This paper addresses sampling-based trajectory optimization for risk-aware navigation under stochastic dynamics. Typically such approaches operate by computing $\tilde{N}$ perturbed rollouts around the nominal dynamics to estimate the…

Robotics · Computer Science 2025-07-15 Basant Sharma , Arun Kumar Singh

Bayesian optimization has emerged as a highly effective tool for the safe online optimization of systems, due to its high sample efficiency and noise robustness. To further enhance its efficiency, reduced physical models of the system can…

Machine Learning · Computer Science 2024-06-18 Jannis O. Lübsen , Christian Hespe , Annika Eichler

Bayesian aggregation lets election forecasters combine diverse sources of information, such as state polls and economic and political indicators: as in our collaboration with The Economist magazine. However, the demands of real-time…

Methodology · Statistics 2025-10-23 Geonhee Han , Andrew Gelman , Aki Vehtari

Recent major oil-spills were tracked using observations with sufficient altitudes over the sea surface, to detect oil slick locations. For oil-spill responders, we propose a captive Unmanned Aerial System, UAS acting like a periscope over a…

Atmospheric and Oceanic Physics · Physics 2013-02-18 Frédéric Muttin

This paper presents a combined ocean and oil model for adaptive placement of sensors in the immediate aftermath of oilspills. A key feature of this model is the ability to correct its predictions of spill location using continual…

Systems and Control · Electrical Eng. & Systems 2019-11-13 Zak Hodgson , David Browne , Inaki Esnaola , Bryn Jones

This paper presents a new resolution strategy for multi-scale streamer discharge simulations based on a second order time adaptive integration and space adaptive multiresolution. A classical fluid model is used to describe plasma…

Numerical Analysis · Mathematics 2012-04-10 Max Duarte , Zdenek Bonaventura , Marc Massot , Anne Bourdon , Stéphane Descombes , Thierry Dumont

This paper presents novel method for distribution-free robust trajectory optimization and control of discrete-time, nonlinear, and non-Gaussian stochastic systems, with closed-loop guarantees on chance constraint satisfaction. Our framework…

Systems and Control · Electrical Eng. & Systems 2026-03-10 Rihan Aaron D'Silva , Hiroyasu Tsukamoto

In environmental studies, realistic simulations are essential for understanding complex systems. Statistical emulation with Gaussian processes (GPs) in functional data models have become a standard tool for this purpose. Traditional…

Applications · Statistics 2024-09-26 R. Jacob Andros , Rajarshi Guhaniyogi , Devin Francom , Donatella Pasqualini