相关论文: An open-source job management framework for parame…
This paper introduces OccCANINE, an open-source tool that maps occupational descriptions to HISCO codes. Manual coding is slow and error-prone; OccCANINE replaces weeks of work with results in minutes. We fine-tune CANINE on 15.8 million…
Applications that fuse machine learning and simulation can benefit from the use of multiple computing resources, with, for example, simulation codes running on highly parallel supercomputers and AI training and inference tasks on…
Bayesian optimization is proposed for automatic learning of optimal controller parameters from experimental data. A probabilistic description (a Gaussian process) is used to model the unknown function from controller parameters to a…
The Pierre Auger Observatory is designed to unveil the nature and the origins of the highest energy cosmic rays. The large and geographically dispersed collaboration of physicists and the wide-ranging collection of simulation and…
The Pierre Auger Observatory is designed to unveil the nature and the origins of the highest energy cosmic rays. The large and geographically dispersed collaboration of physicists and the wide-ranging collection of simulation and…
In this paper we present the Open Software Services for Classrooms and Research (OSSCAR) platform. OSSCAR provides an open collaborative environment to develop, deploy and access educational resources in the form of web applications. To…
This paper presents an open-source, lightweight, yet comprehensive software framework, named RPC, which integrates physics-based simulators, planning and control libraries, debugging tools, and a user-friendly operator interface. RPC…
Process-Aware Information Systems (PAIS) support organizations in managing and automating their processes. A full automation of processes is in particular industries, such as service-oriented markets, not practicable. The integration of…
Learning performant robot manipulation policies can be challenging due to high-dimensional continuous actions and complex physics-based dynamics. This can be alleviated through intelligent choice of action space. Operational Space Control…
We introduce an open source python framework named PHS - Parallel Hyperparameter Search to enable hyperparameter optimization on numerous compute instances of any arbitrary python function. This is achieved with minimal modifications inside…
The increasing number and complexity of planetary exploration space missions require new tools to access, visualize and analyse data to improve their scientific return. ASI Science Data Center (ASDC) addresses this request with the web-tool…
Large parameter space explorations are among the most time consuming yet critically important tasks in many fields of modern research. ExpoCloud enables the researcher to harness cloud compute resources to achieve time and budget-effective…
Extracting information from raw data is probably one of the central activities of experimental scientific enterprises. This work is about a pipeline in which a specific model is trained to provide a compact, essential representation of the…
We describe AMUSE, the Astrophysical Multipurpose Software Environment, a programming framework designed to manage multi-scale, multi-physics simulations in a hierarchical, extensible, and internally consistent way. Constructed as a…
Software Engineering and the implementation of software has become a challenging task as many tools, frameworks and languages must be orchestrated into one functioning piece. This complexity increases the need for testing and analysis…
The parameter space of dynamical systems arising in applications is often found to be high-dimensional and difficult to explore. We construct a fast algorithm to numerically analyze "quantitative features" of dynamical systems depending on…
We present a new modeling paradigm for optimization that we call random field optimization. Random fields are a powerful modeling abstraction that aims to capture the behavior of random variables that live on infinite-dimensional spaces…
Computation-Enabled Object Storage (COS) systems, such as MinIO and Ceph, have recently emerged as promising storage solutions for post hoc, SQL-based analysis on large-scale datasets in High-Performance Computing (HPC) environments. By…
Current practice in parameter space exploration in euclidean space is dominated by randomized sampling or design of experiment methods. The biggest issue with these methods is not keeping track of what part of parameter space has been…
Open source software (OSS) is essential for modern society and, while substantial research has been done on individual (typically central) projects, only a limited understanding of the periphery of the entire OSS ecosystem exists. For…