Search Results for "simulations"
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Showing 59 open source projects for "simulations"
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Brax
Massively parallel rigidbody physics simulation
Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization. -
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NVIDIA PhysicsNeMo
Open-source deep-learning framework for building and training
...PhysicsNeMo provides modular Python components that allow developers to create scalable training and inference pipelines for models that combine data-driven learning with physics-based constraints. It is built on top of the PyTorch ecosystem and integrates with GPU-accelerated computing environments to handle computationally demanding simulations and datasets. The framework supports a wide range of scientific applications, including computational fluid dynamics, climate modeling, weather prediction, and engineering simulations. -
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highway-env
A minimalist environment for decision-making in autonomous driving
HighwayEnv is an OpenAI Gym-compatible environment focused on autonomous driving scenarios. It provides flexible simulations for testing decision-making algorithms in highway, intersection, and merging traffic situations. -
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Future AGI
Open-source platform for evaluating, observing, and improving LLM
Future AGI is an open-source, end-to-end platform for evaluating, observing, protecting, and improving AI agent applications. It is built for teams that need more than basic tracing, combining evaluations, simulations, datasets, guardrails, gateway routing, and optimization in one feedback loop. The platform helps developers detect hallucinations, measure agent quality, monitor production behavior, and use evaluation results to improve prompts or workflows over time. It supports both cloud and self-hosted deployment models, making it useful for teams with different privacy, infrastructure, and compliance needs. ... -
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robosuite
A Modular Simulation Framework and Benchmark for Robot Learning
...Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning. -
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RL Games
RL implementations
rl_games is a high-performance reinforcement learning framework optimized for GPU-based training, particularly in environments like robotics and continuous control tasks. It supports advanced algorithms and is built with PyTorch. -
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MathModelAgent
An Agent Designed for Mathematical Modeling
MathModelAgent is an AI agent system designed specifically for assisting with mathematical modeling tasks and academic problem solving. The platform automates the process of analyzing mathematical problems, constructing models, generating code for simulations or computations, and producing a complete research-style report. The project uses a multi-agent architecture where different specialized agents handle tasks such as problem interpretation, modeling design, programming implementation, and paper writing. Through integration with multiple large language models, the system can coordinate these components to generate structured modeling solutions and formatted research papers suitable for submission. ... -
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ManiSkill
SAPIEN Manipulation Skill Framework
ManiSkill is a benchmark platform for training and evaluating reinforcement learning agents on dexterous manipulation tasks using physics-based simulations. Developed by Hao Su Lab, it focuses on robotic manipulation with diverse, high-quality 3D tasks designed to challenge perception, control, and planning in robotics. ManiSkill provides both low-level control and visual observation spaces for realistic learning scenarios. -
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DiffEqFlux.jl
Pre-built implicit layer architectures with O(1) backprop, GPUs
DiffEqFlux.jl is a Julia library that combines differential equations with neural networks, enabling the creation of neural differential equations (neural ODEs), universal differential equations, and physics-informed learning models. It serves as a bridge between the DifferentialEquations.jl and Flux.jl libraries, allowing for end-to-end differentiable simulations and model training in scientific machine learning. DiffEqFlux.jl is widely used for modeling dynamical systems with learnable components. -
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Diffrax
Numerical differential equation solvers in JAX
Diffrax is a numerical differential equation solving library built for the JAX ecosystem, with a strong focus on composability, differentiability, and high-performance scientific computing. The project provides tools for solving ordinary differential equations, stochastic differential equations, controlled differential equations, and related systems in a way that fits naturally into modern machine learning and differentiable programming workflows. Because it is written to work closely with... -
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Google DeepMind GraphCast and GenCast
Global weather forecasting model using graph neural networks and JAX
...The repository provides complete example code for running and training both GraphCast and GenCast, two models introduced in DeepMind’s research papers. GraphCast is designed to perform high-resolution atmospheric simulations using the ERA5 dataset from ECMWF, while GenCast extends the approach with diffusion-based ensemble forecasting for probabilistic weather prediction. Both models are built on JAX and integrate advanced neural architectures capable of learning from multi-scale geophysical data represented on icosahedral meshes. The package includes pretrained model weights, normalization statistics, and demonstration notebooks that allow users to replicate and fine-tune weather forecasting experiments in Colab or on Google Cloud TPUs and GPUs. -
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VIPER
AI-powered red team platform for adversary simulation toolkit
...Viper emphasizes ease of use through a graphical interface, allowing users to manage complex operations without relying solely on command-line tools. It includes a large collection of built-in modules that cover multiple stages of the MITRE ATT&CK framework, enabling realistic and structured attack simulations. Viper also incorporates automation features and workflow orchestration, helping teams streamline repetitive tasks and maintain continuous monitoring of target environments. A notable aspect of the project is its integration of a large language model agent, which assists with decision-making, parameter handling, and analysis during operations. -
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Materials Discovery: GNoME
AI discovers 520000 stable inorganic crystal structures for research
...The repository provides datasets, model definitions, and interactive Colabs for exploring these materials, computing decomposition energies, and visualizing chemical families. Additionally, it includes JAX-based implementations of GNoME and Nequip—the latter being used to train interatomic potentials for dynamic simulations. -
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HY-World 1.5
A Systematic Framework for Interactive World Modeling
HY-WorldPlay is a Hunyuan AI project focusing on immersive multimodal content generation and interaction within virtual worlds or simulated environments. It aims to empower AI agents with the capability to both understand and generate multimedia content — including text, audio, image, and potentially 3D or game-world elements — enabling lifelike dialogue, environmental interpretations, and responsive world behavior. The platform targets use cases in digital entertainment, game worlds,... -
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Diffusion for World Modeling
Learning agent trained in a diffusion world model
...This approach allows training to occur in a simulated world that captures detailed visual dynamics while reducing the need for costly interactions with real environments. The system has been applied to tasks such as Atari game simulations and demonstrations involving complex environments like first-person shooter games. -
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VibeKit
Run Claude Code, Gemini, Codex in a clean, isolated sandbox
Vibekit is an open-source toolkit focused on rapid prototyping and building of AI-driven experiences, particularly those that integrate multimodal inputs, reactive interfaces, and context-aware behaviors. It provides a set of abstractions and utilities that let developers connect generative models to UI frameworks, sensors, event streams, and external services without having to build plumbing from scratch. Instead of treating AI models as black boxes behind simple prompts, Vibekit encourages... -
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WorldGen
Generate Any 3D Scene in Seconds
WorldGen is an AI model and library that can generate full 3D scenes in a matter of seconds from either text prompts or reference images. It is designed to create interactive environments suitable for games, simulations, robotics research, and virtual reality, rather than just static 3D assets. The core idea is that you describe a world in natural language and WorldGen produces a navigable 3D scene that you can freely explore in 360 degrees, with loop closure so that the space remains consistent as you move around. It supports a wide variety of scenes, including both indoor and outdoor settings, and can handle realistic as well as stylized or fantastical environments. ... -
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EcoLab is a C++ based Agent Based Modelling system, with emphasis on high performance computing for scaling to large simulations.
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Burn To The Brim
Utility for efficiently grouping files and folders together
**Burn To The Brim** is a highly efficient archiving utility designed to solve the classic subset-sum (bin packing) optimization challenge. It intelligently selects and groups files and directories (documents, high-fidelity media, or raw back-ups) to optimally fill recordable Blu-Rays, USB drives or custom-capacity storage drives. By recursively scanning your designated folders, BTTB matches item sizes to your media capacity, finding a near-perfect selection in milliseconds and an... -
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AnyTrading
The most simple, flexible, and comprehensive OpenAI Gym trading
gym-anytrading is an OpenAI Gym-compatible environment designed for developing and testing reinforcement learning algorithms on trading strategies. It simulates trading environments for financial markets, including stocks and forex. -
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CORL
High-quality single-file implementations of SOTA Offline
CORL (Collection of Reinforcement Learning Environments for Control Tasks) is a modular and extensible set of high-quality reinforcement learning environments focused on continuous control and robotics. It aims to offer standardized environments suitable for benchmarking state-of-the-art RL algorithms in control tasks, including physics-based simulations and custom-designed scenarios. -
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Recast Navigation
Navigation mesh generation and pathfinding toolkit for game AI systems
Recast Navigation is an open source toolkit designed for building navigation meshes and performing pathfinding in 3D environments, particularly for video games and simulations. It provides a set of libraries that transform input geometry into navigation meshes that AI agents can use to move through virtual worlds. Its core component, Recast, constructs navigation meshes by rasterizing triangle meshes into voxels, filtering out areas that are not walkable, and converting the remaining regions into polygon meshes suitable for navigation. ... -
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Menagerie
A collection of high-quality models for the MuJoCo physics engine
...The collection spans a wide range of categories including robotic arms, humanoids, quadrupeds, mobile manipulators, drones, and biomechanical systems. Users can access models directly via the robot_descriptions Python package or by cloning the repository for use in interactive MuJoCo simulations. -
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Fedhf
A Flexible Federated Learning Simulator
FedHF is a Python-based simulator for flexible, heterogeneous, and asynchronous federated learning research. It provides configurable resource models, supports asynchronous protocols, and accelerates experimentation. -
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AirSim
A simulator for drones, cars and more, built on Unreal Engine
...It supports software-in-the-loop simulation with popular flight controllers such as PX4 & ArduPilot and hardware-in-loop with PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. AirSim's development is oriented towards the goal of creating a platform for AI research to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles. For this purpose, AirSim also exposes APIs to retrieve data and control vehicles in a platform independent way. ...