Searched for: subject%3A%22Inference%22
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Pezzato, C. (author)
In an ever-evolving society, the demand for autonomous robots equipped with human-level capabilities is becoming increasingly imperative. Various factors, such as an aging population and a shortage of labor for repetitive and physically demanding tasks, have underscored the need for capable autonomous robots to assist us in our daily activities....
doctoral thesis 2024
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Dash, T.K. (author), Driessen, J.N. (author), Krasnov, O.A. (author), Yarovoy, Alexander (author)
The challenge of reconstructing the Doppler spectrum of a precipitation-like event observed by a fast-scanning weather radar is addressed. A novel method is proposed where the echo sequence in time is assumed to be a complex Gaussian process with a known covariance structure. It is a two-step approach where the first step is the estimation of...
conference paper 2024
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Moriaux, Olivier (author), Zamponi, R. (author), Schram, Christophe (author)
The empirical calibration of remote microphone probes (RMP), used to acquire wall-pressure fluctuations, can introduce spurious resonance into the sensor transfer function due to the difference in the pressure field inside the calibrator geometry over multiple calibration steps. Such spurious resonance subsequently propagates into the...
journal article 2024
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Pellegrino, G. (author)
doctoral thesis 2023
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Moreno León, C. (author)
Radar-tracking of low-observable targets such as drones suffers from low detection performance. In these type of applications, it is desirable to avoid data thresholding in order to preserve the weak target signal in the raw sensor data. This thesis considers the Multiple Object Tracking (MOT) problem in the context of radar Track-before-Detect ...
doctoral thesis 2023
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Anil Meera, A. (author)
The potential impact of a grand unified theory of the brain on the robotics community might be immense, as it might hold the key to the general artificial intelligence. Such a theory might make revolutionary leaps in robot intelligence by improving the quality of our lives. The last two decades have witnessed the rise of one such brain theory -...
doctoral thesis 2023
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Pezzato, C. (author), Hernández, Carlos (author), Bonhof, S.D. (author), Wisse, M. (author)
In this article, we propose a hybrid combination of active inference and behavior trees (BTs) for reactive action planning and execution in dynamic environments, showing how robotic tasks can be formulated as a free-energy minimization problem. The proposed approach allows handling partially observable initial states and improves the...
journal article 2023
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Meo, Cristian (author), Franzese, G. (author), Pezzato, C. (author), Spahn, M. (author), Lanillos, Pablo (author)
Adaptation to external and internal changes is of major importance for robotic systems in uncertain environments. Here, we present a novel multisensory active inference (AIF) torque controller for industrial arms that shows how prediction can be used to resolve adaptation. Our controller, inspired by the predictive brain hypothesis, improves...
journal article 2023
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Buijsman, S.N.R. (author)
Machine learning is used more and more in scientific contexts, from the recent breakthroughs with AlphaFold2 in protein fold prediction to the use of ML in parametrization for large climate/astronomy models. Yet it is unclear whether we can obtain scientific explanations from such models. I argue that when machine learning is used to conduct...
journal article 2023
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Wu, Jiansong (author), Cai, Jitao (author), Liu, Z. (author), Yuan, S. (author), Bai, Yiping (author), Zhou, Rui (author)
As an effective way to facilitate the increasing demand for reliable infrastructure, energy supply and sustainable urban development, underground utility tunnels have been developed rapidly in recent years. Due to the widespread distribution of utility tunnels, the safe operation of natural gas pipelines accommodated in utility tunnels has...
journal article 2023
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Oosterwegel, Max J. (author), Krijthe, J.H. (author), den Brok, Melina G.H.E. (author), van den Heuvel, Lieneke (author), Richard, Edo (author), Heskes, Tom (author), Bloem, Bastiaan R. (author), Evers, Luc J.W. (author)
Background: Currently available treatment options for Parkinson's disease are symptomatic and do not alter the course of the disease. Recent studies have raised the possibility that cardiovascular risk management may slow the progression of the disease. Objectives: We estimated the effect of baseline cardiovascular risk factors on the...
journal article 2023
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Zhang, Xinqi (author), Shi, Jihao (author), Huang, Xinyan (author), Xiao, Fu (author), Yang, M. (author), Huang, Jiawei (author), Yin, Xiaokang (author), Sohail Usmani, Asif (author), Chen, Guoming (author)
Deep learning has been widely applied to automated leakage detection and location of natural gas pipe networks. Prevalent deep learning approaches do not consider the spatial dependency of sensors, which limits leakage detection performance. Graph deep learning is a promising alternative to prevailing approaches as it can model spatial...
journal article 2023
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Jia, Xiang Yu (author), Liu, Er Jian (author), Yang, Y. (author), Yan, Xiao Yong (author)
The universal scaling relationship between an attribute and the size of a system is widespread in nature and society and is known as allometric growth. Previous studies have explained that the allometric growth exponent of single-source systems is uniquely determined by the dimension. However, the phenomenon that the exponent shows diversity...
journal article 2023
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Zeng, Cheng (author), Huang, Jinsong (author), Wang, H. (author), Xie, Jiawei (author), Zhang, Yuting (author)
Reliable estimation of rail useful lifetime can provide valuable information for predictive maintenance in railway systems. However, in most cases, lifetime data is incomplete because not all pieces of rail experience failure by the end of the study horizon, a problem known as censoring. Ignoring or otherwise mistreating the censored cases...
journal article 2023
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Tricomi, Pier Paolo (author), Facciolo, Lisa (author), Apruzzese, Giovanni (author), Conti, M. (author)
Did you know that over 70 million of Dota2 players have their in-game data freely accessible? What if such data is used in malicious ways? This paper is the first to investigate such a problem. Motivated by the widespread popularity of video games, we propose the first threat model for Attribute Inference Attacks (AIA) in the Dota2 context....
conference paper 2023
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Igea, Felipe (author), Cicirello, A. (author)
Multi-modal distributions of some physics-based model parameters are often encountered in engineering due to different situations such as a change in some environmental conditions, and the presence of some types of damage and non-linearity. In statistical model updating, for locally identifiable parameters, it can be anticipated that multi...
journal article 2023
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Troost, Christian (author), Huber, Robert (author), Bell, Andrew R. (author), van Delden, Hedwig (author), Filatova, T. (author), Le, Quang Bao (author), Lippe, Melvin (author), Niamir, Leila (author), Polhill, J. Gareth (author), Sun, Zhanli (author), Berger, Thomas (author)
There has so far been no shared understanding of validity in agent-based simulation. We here conceptualise validation as systematically substantiating the premises on which conclusions from simulation analysis for a particular modelling context are built. Given such a systematic perspective, validity of agent-based models cannot be ensured if...
journal article 2023
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Money, Rohan (author), Krishnan, Joshin (author), Beferull-Lozano, Baltasar (author), Isufi, E. (author)
An online topology estimation algorithm for nonlinear structural equation models (SEM) is proposed in this paper, addressing the nonlinearity and the non-stationarity of real-world systems. The nonlinearity is modeled using kernel formulations, and the curse of dimensionality associated with the kernels is mitigated using random feature...
journal article 2023
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Yang, Qiuling (author), Coutino, Mario (author), Leus, G.J.T. (author), Giannakis, Georgios B. (author)
Graph-based learning and estimation are fundamental problems in various applications involving power, social, and brain networks, to name a few. While learning pair-wise interactions in network data is a well-studied problem, discovering higher-order interactions among subsets of nodes is still not yet fully explored. To this end, encompassing...
journal article 2023
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Bouwmeester, J. (author), Menicucci, A. (author), Gill, E.K.A. (author)
The objective of this paper is to investigate which approach would lead to more reliable CubeSats: full subsystem redundancy or improved testing. Based on data from surveys, the reliability of satellites and subsystems is estimated using a Kaplan–Meier estimator. Subsequently, a variety of reliability models is defined and their maximum...
journal article 2022
Searched for: subject%3A%22Inference%22
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