技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: atomistic-simulations

英文目录

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

19K
Stars
79/100
信任
分类: ml-automation审计

Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.

2.4K
Stars
84/100
信任
分类: development审计

Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.

1.2K
Stars
85/100
信任
分类: devops审计

Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.

907
Stars
69/100
信任
分类: data-analysis审计

A flyweight in situ visualization and analysis runtime for multi-physics HPC simulations

255
Stars
72/100
信任
分类: geo-science审计

Cosmos-Transfer2.5, built on top of Cosmos-Predict2.5, produces high-quality world simulations conditioned on multiple spatial control inputs.

684
Stars
73/100
信任
分类: media-automation审计

Foam-Agent: An end-to-end, composable multi-agent framework for automating CFD simulations in OpenFOAM. NeurIPS 2025 Machine Learning and the Physical Sciences Workshop.

260
Stars
70/100
信任
分类: agent-frameworks审计

Simplified Data Exchange for HPC Simulations

244
Stars
65/100
信任
分类: geo-science审计

DScribe is a python package for creating machine learning descriptors for atomistic systems.

467
Stars
69/100
信任
分类: ml-automation审计

Intergrating Atomistic Skills into Agentic IDEs (Cursor, Claude Code, Google Antigravity, OpenClaw, etc)

109
Stars
70/100
信任
分类: development审计

Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, Heston

223
Stars
69/100
信任
分类: finance审计

Numerical simulations using flexible Lattice Boltzmann solvers

171
Stars
64/100
信任
分类: geo-science审计