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The aim of this paper is to propose an adaptation of the well known adaptive conformal inference (ACI) algorithm to achieve finite-sample coverage guarantees in multi-step ahead time-series forecasting in the online setting. ACI dynamically…

Machine Learning · Statistics 2024-09-24 Johan Hallberg Szabadváry

Data-driven visual odometry (VO) is a critical subroutine for autonomous edge robotics, and recent progress in the field has produced highly accurate point predictions in complex environments. However, emerging autonomous edge robotics…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Alex C. Stutts , Danilo Erricolo , Theja Tulabandhula , Amit Ranjan Trivedi

Next-generation solar spectrographs increasingly record dense wavelength windows in which tens to hundreds of spectral lines are sampled at each spatial location and time step. This expands the scope for multi-line, multi-height diagnostics…

Underwater robot interventions require a high level of safety and reliability. A major challenge to address is a robust and accurate acquisition of localization estimates, as it is a prerequisite to enable more complex tasks, e.g. floating…

Robotics · Computer Science 2019-06-13 Arturo Gomez Chavez , Qingwen Xu , Christian A. Mueller , Sören Schwertfeger , Andreas Birk

Beamforming-capable antenna arrays with many elements enable higher data rates in next generation 5G and 6G networks. In current practice, analog beamforming uses a codebook of pre-configured beams with each of them radiating towards a…

Machine Learning · Computer Science 2025-12-08 Alexander Mattick , George Yammine , Georgios Kontes , Setareh Maghsudi , Christopher Mutschler

The Vera C. Rubin Observatory will, over a period of 10 years, repeatedly survey the southern sky. To ensure that images generated by Rubin meet the quality requirements for precision science, the observatory will use an Active Optics…

Sub-wavelength diffractive optics meta-optics present a multi-scale optical system, where the behavior of constituent sub-wavelength scatterers, or meta-atoms, need to be modelled by full-wave electromagnetic simulations, whereas the whole…

The efficiency of the management of top-class ground-based astronomical facilities supported by Adaptive Optics (AO) relies on our ability to forecast the optical turbulence (OT) and a set of relevant atmospheric parameters. Indeed, in…

Instrumentation and Methods for Astrophysics · Physics 2020-06-14 E. Masciadri , G. Martelloni , A. Turchi

Recent successes in machine learning have led to a shift in the design of autonomous systems, improving performance on existing tasks and rendering new applications possible. Data-focused approaches gain relevance across diverse, intricate…

Machine Learning · Computer Science 2019-04-17 Markus Wulfmeier

Phase imaging techniques extract the optical path-length information of a scene, whereas wavefront sensors provide the shape of an optical wavefront. Since these two applications have different technical requirements, they have developed…

Optics · Physics 2018-02-28 F. Soldevila , V. Durán , P. Clemente , J. Lancis , E. Tajahuerce

We propose a data-driven optimization-based pre-compensation method to improve the contour tracking performance of precision motion stages by modifying the reference trajectory and without modifying any built-in low-level controllers. The…

Systems and Control · Electrical Eng. & Systems 2022-09-07 Samuel Balula , Dominic Liao-McPherson , Alisa Rupenyan , John Lygeros

We consider online convex optimization with time-varying stage costs and additional switching costs. Since the switching costs introduce coupling across all stages, multi-step-ahead (long-term) predictions are incorporated to improve the…

Machine Learning · Computer Science 2020-11-26 Yingying Li , Na Li

One of the main limitations of utilizing optimal wavefront shaping in imaging and authentication applications is the slow speed of the optimization algorithms currently being used. To address this problem we develop a micro-genetic…

The use of Fourier methods in wave-front reconstruction can significantly reduce the computation time for large telescopes with a high number of degrees of freedom. However, Fourier algorithms for discrete data require a rectangular data…

Instrumentation and Methods for Astrophysics · Physics 2017-06-07 Charlotte Z. Bond , Carlos M. Correia , Jean-François Sauvage , Benoit Neichel , Thierry Fusco

In powder diffraction data analysis, phase identification is the process of determining the crystalline phases in a sample using its characteristic Bragg peaks. For multiphasic spectra, we must also determine the relative weight fraction of…

Machine Learning · Computer Science 2022-10-21 Patrick Hosein , Jaimie Greasley

Kernels are efficient in representing nonlocal dependence and they are widely used to design operators between function spaces. Thus, learning kernels in operators from data is an inverse problem of general interest. Due to the nonlocal…

Machine Learning · Statistics 2024-10-21 Neil K. Chada , Quanjun Lang , Fei Lu , Xiong Wang

Quantitative evaluations of differences and/or similarities between data samples define and shape optimisation problems associated with learning data distributions. Current methods to compare data often suffer from limitations in capturing…

Machine Learning · Computer Science 2024-01-23 Deborah Pelacani Cruz , George Strong , Oscar Bates , Carlos Cueto , Jiashun Yao , Lluis Guasch

The main objective of the present project is to explore the viability of an adaptive optics control system based exclusively on Field Programmable Gate Arrays (FPGAs), making strong use of their parallel processing capability. In an…

Instrumentation and Methods for Astrophysics · Physics 2018-07-03 Avinash Surendran , Mahesh P. Burse , A. N. Ramaprakash , Padmakar Parihar

To exploit the thousand-fold increase in spectral brightness of modern light sources, increasingly intricate experiments are being conducted that demand extremely precise beam trajectory. Maintaining the optimal trajectory over several…

Semantic segmentation is a well-addressed topic in the computer vision literature, but the design of fast and accurate video processing networks remains challenging. In addition, to run on embedded hardware, computer vision models often…

Computer Vision and Pattern Recognition · Computer Science 2022-06-20 Evann Courdier , François Fleuret
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