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Approximate Bayesian computation (ABC) using a sequential Monte Carlo method provides a comprehensive platform for parameter estimation, model selection and sensitivity analysis in differential equations. However, this method, like other…

Machine Learning · Statistics 2015-07-21 Sanmitra Ghosh , Srinandan Dasmahapatra , Koushik Maharatna

An upgraded GARFIELD + Ring Counter (RCo) apparatus is presented with improved performances as far as electronics and detectors are concerned. On one side fast sampling digital read out has been extended to all detectors, allowing for an…

This paper proposes novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical…

Machine Learning · Computer Science 2024-07-18 Hwanwoo Kim , Daniel Sanz-Alonso

We propose a beam codebook design for integrated sensing and communication (ISAC) that reduces self-interference (SI) to alleviate analog distortion. Our optimization framework, which considers either tapered beamforming or phased arrays…

Signal Processing · Electrical Eng. & Systems 2025-11-04 Rodrigo Hernangómez , Jochen Fink , Renato L. G. Cavalcante , Sławomir Stańczak

Efficient parameter identification of electrochemical models is crucial for accurate monitoring and control of lithium-ion cells. This process becomes challenging when applied to complex models that rely on a considerable number of…

Systems and Control · Electrical Eng. & Systems 2024-05-20 Jianzong Pi , Samuel Filgueira da Silva , Mehmet Fatih Ozkan , Abhishek Gupta , Marcello Canova

High-intensity laser systems present unique measurement and optimization challenges due to their high complexity, low repetition rates, and shot-to-shot variations. We discuss recent developments towards a unified framework based on…

Optics · Physics 2025-06-06 A. Döpp , C. Eberle , J. Esslinger , S. Howard , F. Irshad , J. Schroeder , N. Weisse , S. Karsch

We present a new shear calibration method based on machine learning. The method estimates the individual shear responses of the objects from the combination of several measured properties on the images using supervised learning. The…

Cosmology and Nongalactic Astrophysics · Physics 2020-11-25 Arnau Pujol , Jerome Bobin , Florent Sureau , Axel Guinot , Martin Kilbinger

Machine learning methods usually depend on internal parameters -- so called hyperparameters -- that need to be optimized for best performance. Such optimization poses a burden on machine learning practitioners, requiring expert knowledge,…

Chemical Physics · Physics 2020-04-03 Annika Stuke , Patrick Rinke , Milica Todorović

The robust conjugate direction search (RCDS) method has high tolerance to noise in beam experiments. It has been demonstrated that this method can be used to optimize the machine performance of a light source online. In our study, taking…

Accelerator Physics · Physics 2016-04-19 Hong-Fei Ji , Yi Jiao , Sheng Wang , Da-Heng Ji , Cheng-Hui Yu , Yuan Zhang , Xiao-Biao Huang

This paper presents an automated, model-free, data-driven method for the safe tuning of PID cascade controller gains based on Bayesian optimization. The optimization objective is composed of data-driven performance metrics and modeled using…

Systems and Control · Electrical Eng. & Systems 2021-08-12 Christopher König , Mohammad Khosravi , Markus Maier , Roy S. Smith , Alisa Rupenyan , John Lygeros

Bird's-Eye-View (BEV) semantic segmentation provides comprehensive environmental perception for autonomous driving but suffers multi-modal misalignment and sensor noise. We propose RESAR-BEV, a progressive refinement framework that advances…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Zhiwen Zeng , Yunfei Yin , Zheng Yuan , Argho Dey , Xianjian Bao

Bayesian Optimal Experimental Design (BOED) is a powerful tool to reduce the cost of running a sequence of experiments. When based on the Expected Information Gain (EIG), design optimization corresponds to the maximization of some…

Machine Learning · Statistics 2025-03-14 Jacopo Iollo , Christophe Heinkelé , Pierre Alliez , Florence Forbes

Bose-Einstein condensation (BEC) is a powerful tool for a wide range of research activities, a large fraction of which are related to quantum simulations. Various problems may benefit from different atomic species, but cooling down novel…

Atomic and Molecular Clusters · Physics 2020-07-22 E. T. Davletov , V. V. Tsyganok , V. A. Khlebnikov , D. A. Pershin , D. V. Shaykin , A. V. Akimov

Integrated sensing and communication (ISAC) has been recognized as one of the key technologies for future wireless networks, which potentially need to operate in multiple frequency bands to satisfy ever-increasing demands for both…

Information Theory · Computer Science 2025-07-11 Nemanja Stefan Perović , Mark F. Flanagan , Le-Nam Tran

Diffractive lenses have recently been applied to the domain of multispectral imaging in the X-ray and UV regimes where they can achieve very high resolution as compared to reflective and refractive optics. Conventionally, spectral…

Image and Video Processing · Electrical Eng. & Systems 2020-05-26 Evan Widloski , Ulas Kamaci , Farzad Kamalabadi

We describe a method for searching the optimal hyper-parameters in reservoir computing, which consists of a Gaussian process with Bayesian optimization. It provides an alternative to other frequently used optimization methods such as grid,…

Machine Learning · Computer Science 2017-06-15 Jan Yperman , Thijs Becker

Currently, an excessive amount of event data is being obtained in four-dimensional inelastic neutron-scattering experiments. A method for automatic bin-width optimization of multidimensional histograms has been developed and recently…

Data Analysis, Statistics and Probability · Physics 2026-03-19 Kensuke Muto , Hirotaka Sakamoto , Kenji Nagata , Taka-hisa Arima , Masato Okada

The transient behavior of Automatic Generation Control (AGC) systems is a critical aspect of power system operation. Therefore, fully extracting the potential of Battery Energy Storage Systems (BESSs) for AGC enhancement is of paramount…

Systems and Control · Electrical Eng. & Systems 2025-09-27 Yiqiao Xu , Alessandra Parisio , Zhongguo Li , Zhen Dong , Zhengtao Ding

It has long been a challenging task to improve the light collection efficiency of conventional image sensors built with color filters that inevitably cause the energy loss of out-of-band photons. Although various schemes have been proposed…

Backaction-evading (BAE) measurements of a mechanical resonator, by continuously monitoring a single quadrature of motion, can achieve precision below the zero-point uncertainty. When this happens, the measurement leaves the resonator in a…

Quantum Physics · Physics 2021-02-25 Antonio Di Giovanni , Matteo Brunelli , Marco G. Genoni