Phoenics: Bayesian optimization for efficient experiment planning
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Updated
Jul 3, 2019 - Python
Phoenics: Bayesian optimization for efficient experiment planning
A Codex/Claude skill for thermal-fluid mechanical engineering research, proposal development, technical writing, data analysis, presentations, and AI-assisted workflows.
A bilingual (EN/ZH) 4-stage research workflow skill for Claude Code and Codex CLI — topic refinement, urgency assessment, route evaluation, and experiment planning with citation verification
Experiment Planning Theory Labs
Agent plugin for paper-level experiment planning, claim-evidence mapping, baselines, ablations, figures, and task handoff.
Лабораторные работы по предмету "Планирование эксперимента" с А.В. Куровым 8 семестр 2021-2022 уч.г.
Turn scientific hypotheses into literature-backed experiment plans, with catalog checks, budgets, and scientist feedback in a desktop workspace.
Plan AI research validation within a time budget: predictions, falsifiers, observations and JSON/Markdown handoffs. 支持 iPolloWork 的中英双语假设验证队列插件。
论文证据驱动的科研工作流 Agent / Paper-grounded research workflow agent for code analysis, safe experiment planning, metric parsing, verification, and reproduction reporting
Autoresearch tools for 3D medical imaging segmentation with MIST.
To associate your repository with the experiment-planning topic, visit your repo's landing page and select "manage topics."