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HyperNetX (HNX) is an open source Python library for the analysis and visualization of complex network data modeled as hypergraphs. Initially released in 2019, HNX facilitates exploratory data analysis of complex networks using algebraic…

Mathematical Software · Computer Science 2023-10-19 Brenda Praggastis , Sinan Aksoy , Dustin Arendt , Mark Bonicillo , Cliff Joslyn , Emilie Purvine , Madelyn Shapiro , Ji Young Yun

Procedural models (i.e. symbolic programs that output visual data) are a historically-popular method for representing graphics content: vegetation, buildings, textures, etc. They offer many advantages: interpretable design parameters,…

Simulation is a foundational tool for the analysis and testing of cyber-physical systems (CPS), underpinning activities such as algorithm development, runtime monitoring, and system verification. As CPS grow in complexity and scale,…

Software Engineering · Computer Science 2025-06-13 Quinn Thibeault , Giulia Pedrielli

High-fidelity computational fluid dynamics (CFD) is widely used for thermal-fluid design, but repeated CFD solves remain expensive for design optimization, uncertainty analysis, and digital-twin workflows. Recently, our team has…

Fluid Dynamics · Physics 2026-05-28 Daniel Curl , Han Hu

In recent years, x-ray speckle tracking techniques have emerged as viable tools for wavefront metrology and sample imaging applications. These methods are based on the measurement of near-field images. Thanks to the simple experimental…

Image and Video Processing · Electrical Eng. & Systems 2020-03-31 Andrew J. Morgan , Kevin T. Murray , Harry M. Quiney , Saša Bajt , Henry N. Chapman

Power laws are theoretically interesting probability distributions that are also frequently used to describe empirical data. In recent years effective statistical methods for fitting power laws have been developed, but appropriate use of…

Data Analysis, Statistics and Probability · Physics 2014-02-03 Jeff Alstott , Ed Bullmore , Dietmar Plenz

Probabilistic graphical models (PGMs) have become a popular tool for computational analysis of biological data in a variety of domains. But, what exactly are they and how do they work? How can we use PGMs to discover patterns that are…

Quantitative Methods · Quantitative Biology 2010-02-22 Edoardo M Airoldi

Model-based methods are the dominant paradigm for controlling robotic systems, though their efficacy depends heavily on the accuracy of the model used. Deep neural networks have been used to learn models of robot dynamics from data, but…

Robotics · Computer Science 2020-04-23 Jayesh K. Gupta , Kunal Menda , Zachary Manchester , Mykel J. Kochenderfer

The udkm1Dsim toolbox is a collection of Python classes and routines to simulate the thermal, structural, and magnetic dynamics after laser excitation as well as the according X-ray scattering response in one-dimensional sample structures.…

Computational Physics · Physics 2021-05-31 Daniel Schick

Recently, the integration of advanced simulation technologies with artificial intelligence (AI) is revolutionizing science and engineering research. ChronoLlama introduces a novel framework that customizes the open-source LLMs, specifically…

Software Engineering · Computer Science 2025-01-09 Jingquan Wang , Harry Zhang , Khailanii Slaton , Shu Wang , Radu Serban , Jinlong Wu , Dan Negrut

Visualization plays a relevant role for discovering patterns in big sets of data. In fact, the most common way to help a human with a pattern interpretation is through a graphic. In 2D/3D virtual environments for procedural training the…

Human-Computer Interaction · Computer Science 2025-12-24 Diego Riofrío-Luzcando , Jaime RamÍrez , Cristian Moral , Angélica de Antonio , Marta Berrocal-Lobo

TensorX is a Python library for prototyping, design, and deployment of complex neural network models in TensorFlow. A special emphasis is put on ease of use, performance, and API consistency. It aims to make available high-level components…

Machine Learning · Computer Science 2021-01-05 Davide Nunes , Luis Antunes

Accurate physical modeling with 3D-printing techniques could lead to new approaches to study structure and dynamics of biological systems complementing computational methods. Computational biology has become an important part of research…

Other Computer Science · Computer Science 2015-07-14 Promita Chakraborty

HOTTBOX is a Python library for exploratory analysis and visualisation of multi-dimensional arrays of data, also known as tensors. The library includes methods ranging from standard multi-way operations and data manipulation through to…

Mathematical Software · Computer Science 2021-12-02 Ilya Kisil , Giuseppe G. Calvi , Bruno S. Dees , Danilo P. Mandic

bayesian_pyhf is a Python package that allows for the parallel Bayesian and frequentist evaluation of multi-channel binned statistical models. The Python library pyhf is used to build such models according to the HistFactory framework and…

Computation · Statistics 2023-12-13 Matthew Feickert , Lukas Heinrich , Malin Horstmann

Complex systems are usually represented as an intricate set of relations between their components forming a complex graph or network. The understanding of their functioning and emergent properties are strongly related to their structural…

Data Analysis, Statistics and Probability · Physics 2014-01-08 Sergio Gomez , Alberto Fernandez , Clara Granell , Alex Arenas

In computer graphics (CG) education, the challenge of finding modern, versatile tools is significant, particularly when integrating both legacy and advanced technologies. Traditional frameworks, often reliant on solid, yet outdated APIs…

Graphics · Computer Science 2024-09-26 John Petropoulos , Manos Kamarianakis , Antonis Protopsaltis , George Papagiannakis

We provided a concise and self-contained introduction to molecular dynamics (MD) simulation, which involves a body of fundamentals needed for all MD users. The associated computer code, simulating a gas of classical particles interacting…

Materials Science · Physics 2021-04-01 Ashkan Shekaari , Mahmoud Jafari

Coupled natural systems are generally modeled at multiple abstraction levels. Both structural scale and behavioral complexity of these models are determinants in the kinds of questions that can be posed and answered. As scale and complexity…

Computational Engineering, Finance, and Science · Computer Science 2018-07-23 Hessam S. Sarjoughian , William A. Boyd , Miguel F. Acevedo

Modeling complex physical dynamics is a fundamental task in science and engineering. Traditional physics-based models are sample efficient, and interpretable but often rely on rigid assumptions. Furthermore, direct numerical approximation…

Machine Learning · Computer Science 2023-03-02 Rui Wang , Rose Yu
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