--- title: "RoBO vs rembo" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/automl-robo-vs-ziyuw-rembo" tools: ["automl-robo", "ziyuw-rembo"] --- # RoBO vs rembo *GraphCanon updated Aug 4, 2026* ## Verdict Pick RoBO if roBO is a Python framework for robust Bayesian optimization using Gaussian processes and random forests; pick rembo if rembo is a Matlab-based tool for high-dimensional Bayesian optimization using random embedding. [RoBO](https://github.com/automl/RoBO) reports 492 GitHub stars, 129 forks, and 25 open issues, last pushed Apr 30, 2019. [rembo](https://github.com/ziyuw/rembo) has 117 stars, 25 forks, and 3 open issues, last pushed Aug 4, 2013. Figures are from public GitHub metadata via [RoBO's repository](https://github.com/automl/RoBO) and [rembo's repository](https://github.com/ziyuw/rembo). | | [RoBO](/tools/automl-robo.md) | [rembo](/tools/ziyuw-rembo.md) | | --- | --- | --- | | Tagline | A Robust Bayesian Optimization framework | Bayesian optimization in high-dimensions via random embedding. | | Stars | 492 | 117 | | Forks | 129 | 25 | | Open issues | 25 | 3 | | Language | Python | Matlab | | Adopt for | RoBO is a Python framework for robust Bayesian optimization using Gaussian processes and random forests. | Rembo is a Matlab-based tool for high-dimensional Bayesian optimization using random embedding. | | Persona | - | - | | Runtime | - | - | | License | BSD-3-Clause | - | | Categories | Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [RoBO](/tools/automl-robo.md) | [rembo](/tools/ziyuw-rembo.md) | | --- | --- | --- | | Days since push | 2653d | 4747d | | Open issues (now) | 25 | 3 | | Owner type | Organization | User | | Full report | [trust report](/tools/automl-robo/trust.md) | [trust report](/tools/ziyuw-rembo/trust.md) | ## Decision facts: RoBO - **Adopt for:** RoBO is a Python framework for robust Bayesian optimization using Gaussian processes and random forests. ## Decision facts: rembo - **Adopt for:** Rembo is a Matlab-based tool for high-dimensional Bayesian optimization using random embedding. ## Choose when ### Choose RoBO if… - RoBO is primarily Python; rembo is Matlab. - Tags unique to RoBO: gaussian processes, python, random forests. - For tasks requiring robust handling of noisy data in Bayesian Optimization ### Choose rembo if… - rembo is primarily Matlab; RoBO is Python. - Tags unique to rembo: high-dimensional space, random embedding. - When working with high-dimensional data spaces that require efficient exploration and optimization, making it ideal for problems exceeding typical dimensions ## When NOT to use RoBO - Avoid if your project strictly requires open-source licenses other than BSD-3-Clause - Not suitable for users not comfortable installing external dependencies manually ## When NOT to use rembo - For low-dimensional spaces where full Bayesian optimization methods would be more efficient and less complex than random embedding - In scenarios requiring open-source or licensed software when Rembo's license status is unknown, potentially limiting its use in certain projects ## Common questions ### What is the difference between RoBO and rembo? RoBO: A Robust Bayesian Optimization framework. rembo: Bayesian optimization in high-dimensions via random embedding.. See the comparison table for live GitHub stats and shared categories. ### When should I choose RoBO over rembo? Choose RoBO over rembo when RoBO is primarily Python; rembo is Matlab; Tags unique to RoBO: gaussian processes, python, random forests; For tasks requiring robust handling of noisy data in Bayesian Optimization. ### When should I choose rembo over RoBO? Choose rembo over RoBO when rembo is primarily Matlab; RoBO is Python; Tags unique to rembo: high-dimensional space, random embedding; When working with high-dimensional data spaces that require efficient exploration and optimization, making it ideal for problems exceeding typical dimensions. ### When should I avoid RoBO? Avoid if your project strictly requires open-source licenses other than BSD-3-Clause Not suitable for users not comfortable installing external dependencies manually ### When should I avoid rembo? For low-dimensional spaces where full Bayesian optimization methods would be more efficient and less complex than random embedding In scenarios requiring open-source or licensed software when Rembo's license status is unknown, potentially limiting its use in certain projects ### Is RoBO or rembo more popular on GitHub? RoBO has more GitHub stars (492 vs 117). Stars measure visibility, not whether either tool fits your constraints. ### Are RoBO and rembo open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to RoBO or rembo? GraphCanon lists graph-backed alternatives at [RoBO alternatives](/tools/automl-robo/alternatives) and [rembo alternatives](/tools/ziyuw-rembo/alternatives) ([RoBO markdown twin](/tools/automl-robo/alternatives.md), [rembo markdown twin](/tools/ziyuw-rembo/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/automl-robo-vs-ziyuw-rembo.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, RoBO or rembo? RoBO: Dormant. rembo: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for RoBO and rembo? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [RoBO trust report](/tools/automl-robo/trust); [rembo trust report](/tools/ziyuw-rembo/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=automl-robo`](/api/graphcanon/graph?tool=automl-robo) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_