Simulation refers to the process of creating a virtual model of a real-world system to study its behavior and performance under various conditions. This topic covers the principles, methodologies, and applications of simulation in fields such as engineering, science, healthcare, and social sciences. Simulations can range from simple models to complex, interactive environments, allowing researchers and practitioners to test hypotheses, train individuals, and predict outcomes without the risks or costs associated with real-world experiments. The topic also explores different types of simulation software and tools, as well as best practices for designing and validating simulations.
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
A tool that allows you to create vulnerable instrumented local or cloud environments to simulate attacks against and collect the data into Splunk
A python module for scientific analysis of 3D data based on VTK and Numpy
⚛️ A module for solving and visualizing the Schrödinger equation.
Cryptocurrency trading bot with a graphical user interface with support for simulations, backtests, optimizations, and running live bots.
The perfect sidekick to your scientific inquiries
[ICRA 2022] An opensource framework for cooperative detection. Official implementation for OPV2V.
A curated list of 3D Vision papers relating to Robotics domain in the era of large models i.e. LLMs/VLMs, inspired by awesome-computer-vision, including papers, codes, and related websites
A Control Systems Toolbox for Julia
Learn how to use CARLA with basic APIs
Implementation of Apple's Learning from Simulated and Unsupervised Images through Adversarial Training
🔬 Research Framework for Single and Multi-Players 🎰 Multi-Arms Bandits (MAB) Algorithms, implementing all the state-of-the-art algorithms for single-player (UCB, KL-UCB, Thompson...) and multi-player (MusicalChair, MEGA, rhoRand, MCTop/RandTopM etc).. Available on PyPI: https://pypi.org/project/SMPyBandits/ and documentation on
Julia for optimization simulation and modeling of PowerSystems. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.
Scientific Computing for Chemists is a free text for teaching basic computing skills to chemists using Python, Jupyter notebooks, and the other Python packages. This text makes use of a variety of packages including NumPy, SciPy, matplotlib, pandas, seaborn, nmrglue, SymPy, scikit-image, and scikit-learn.
Enable decision-making based on simulations
Computing reachable states of dynamical systems in Julia
A curated list of software emulators and simulators of PCs, home computers, mainframes, consoles, robots and much more...
Julia package to run Dynamic Power System simulations. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.
Astrophysical Multipurpose Software Environment. This is the main repository for AMUSE
Created by The scientific and engineering community