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Scientists and engineers use simulators to model empirically observed phenomena. However, tuning the parameters of a simulator to ensure its outputs match observed data presents a significant challenge. Simulation-based inference (SBI)…
We present IMTLab, an open-source end-to-end interactive machine translation (IMT) system platform that enables researchers to quickly build IMT systems with state-of-the-art models, perform an end-to-end evaluation, and diagnose the…
We describe the open-source global fitting package GAMBIT: the Global And Modular Beyond-the-Standard-Model Inference Tool. GAMBIT combines extensive calculations of observables and likelihoods in particle and astroparticle physics with a…
Information technology and data science development stimulate transformation in many fields of scientific knowledge. In recent years, a large number of specialized systems for information and knowledge management have been created in…
We introduce Matched Machine Learning, a framework that combines the flexibility of machine learning black boxes with the interpretability of matching, a longstanding tool in observational causal inference. Interpretability is paramount in…
Test optimization contains test case selection and minimization, which is an important challenge in software testing and has been addressed with search-based approaches intensively in the past. Inspired by the recent advancement of using…
In software and hardware development MATLAB and Simulink are used to model cyber physical systems for many years, , especially in automation technology and the automotive industry. Compliance with the required product quality and project…
We present an open-source computer program written in Python language for quantum measurement and related issues. In our program, quantum states and operators, including quantum gates, can be developed into a quantum-object function…
LIBS2ML is a library based on scalable second order learning algorithms for solving large-scale problems, i.e., big data problems in machine learning. LIBS2ML has been developed using MEX files, i.e., C++ with MATLAB/Octave interface to…
Evaluating time series attribution methods is difficult because real-world datasets rarely provide ground truth for which time points drive a prediction. A common workaround is to generate synthetic data where class-discriminating features…
We introduce HexaLab: a WebGL application for real time visualization, exploration and assessment of hexahedral meshes. HexaLab can be used by simply opening www.hexalab.net. Our visualization tool targets both users and scholars.…
swdatatoolkit is a Python-based scientific software library designed to support the acquisition, preprocessing, and analysis of solar and space weather data. The toolkit consolidates functionality across multiple domains, including data…
Time series, characterized by a sequence of data points organized in a discrete-time order, are ubiquitous in real-world scenarios. Unlike other data modalities, time series present unique challenges in learning and modeling due to their…
Scientific workflows facilitate computational, data manipulation, and sometimes visualization steps for scientific data analysis. They are vital for reproducing and validating experiments, usually involving computational steps in scientific…
Many internet applications are powered by machine learned models, which are usually trained on labeled datasets obtained through either implicit / explicit user feedback signals or human judgments. Since societal biases may be present in…
For over 15 years, the mlpack machine learning library has served as a "swiss army knife" for C++-based machine learning. Its efficient implementations of common and cutting-edge machine learning algorithms have been used in a wide variety…
In today's digital landscape, the importance of timely and accurate vulnerability detection has significantly increased. This paper presents a novel approach that leverages transformer-based models and machine learning techniques to…
We present the API for MUSICNTWRK, a python library for pitch class set and rhythmic sequences classification and manipulation, the generation of networks in generalized music and sound spaces, deep learning algorithms for timbre…
MATI (Microstructural Analysis Toolbox for Imaging) is a versatile MATLAB-based toolbox that combines both simulation and data fitting capabilities for microstructural dMRI research. It provides a user-friendly, GUI-driven interface that…
The increasing importance of Computational Science and Engineering has highlighted the need for high-quality scientific software. However, research software development is often hindered by limited funding, time, staffing, and technical…