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Deep research has emerged as a transformative capability for autonomous agents, empowering Large Language Models to navigate complex, open-ended tasks. However, realizing its full potential is hindered by critical limitations, including…
The Atacama Cosmology Telescope is a project to map the microwave background radiation at arcminute angular resolution and high sensitivity in three frequency bands over substantial sky areas. Cosmological signals driving such an experiment…
In this paper, we propose SEA, a novel approach for active robot exploration through semantic map prediction and a reinforcement learning-based hierarchical exploration policy. Unlike existing learning-based methods that rely on one-step…
Machine learning (ML) and AI toolboxes such as scikit-learn or Weka are workhorses of contemporary data scientific practice -- their central role being enabled by usable yet powerful designs that allow to easily specify, train and validate…
Understanding the applicability and limitations of electronic-structure methods needs careful and efficient comparison with accurate reference data. Knowledge of the quality and errors of electronic-structure calculations is crucial to…
SPACE (SPectroscopic All-sky Cosmic Explorer) is a class-M mission proposed to ESA for the Cosmic Vision 2015-2025 call and recently promoted to the next assessment study phase. SPACE will produce the first all-sky spectroscopic survey of…
Over the last three decades comprehensive research has been carried out trying to improve commissioning processes with powerful modeling tools and methodologies for data analysis and visualization. Typically addressed application scenarios…
The study of Mandelbrot Sets (MS) is a promising new approach to the phase transition theory. We suggest two improvements which drastically simplify the construction of MS. They could be used to modify the existing computer programs so that…
This talk summarizes the status of the standard model predictions for electroweak precision observables including g-2 for muons, and discusses the status of the standard model and the MSSM in view of the new data.
Information exploration tasks are inherently complex, ill-structured, and involve sequences of actions usually spread over many sessions. When exploring a dataset, users tend to experiment higher degrees of uncertainty, mostly raised by…
Computer simulators can be computationally intensive to run over a large number of input values, as required for optimization and various uncertainty quantification tasks. The standard paradigm for the design and analysis of computer…
This work contains the details and results of my master's project on testing the IMAGINE pipeline for Galactic magnetic field estimation. The project was carried out from early 2016 to early 2017. For it, an unpublished early development…
State space models (SSMs) with selection mechanisms and hardware-aware architectures, namely Mamba, have recently demonstrated significant promise in long-sequence modeling. Since the self-attention mechanism in transformers has quadratic…
This document details the planning phase of a Systematic Mapping Study. Our goal is to identify and to understand the benefits that the software engineering community has reported on the application of the different reuse strategies in…
This paper presents the components of a newly developed Malaysian SMEs - Software Process Improvement model (MSME-SPI) that can assess SMEs soft-ware development industry in managing and improving their software processes capability. The…
The Multi Unit Spectroscopic Explorer (MUSE) is an integral-field spectrograph operating in the visible wavelength range, and installed at the Very Large Telescope (VLT). The official MUSE pipeline is available from ESO. However, for the…
This paper introduces a methodology to develop energy models for the design space exploration of embedded many-core systems. The design process of such systems can benefit from sophisticated models. Software and hardware can be specifically…
Recently, a framework for application-oriented optimal experiment design has been introduced. In this context, the distance of the estimated system from the true one is measured in terms of a particular end-performance metric. This…
The beam diagnostics system for the Double ElectroStatic Ion Ring ExpEriment (DESIREE) project under construction is briefly described. A system which can operate over a wide range of beam intensities and energies for the DESIREE has been…
Context: Advancements in machine learning (ML) lead to a shift from the traditional view of software development, where algorithms are hard-coded by humans, to ML systems materialized through learning from data. Therefore, we need to…