bifold-pathomics/PathoROB: v0.0.1
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| Auteurs principaux: | , , , , , , |
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| Format: | Recurso digital |
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Zenodo
2026
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| _version_ | 1866901629943414784 |
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| author | Julius Hense beatriz-aignx Edwin D. de Jong Han1Mar jonahkoemen benetti-a Lorenz Linhardt |
| author_facet | Julius Hense beatriz-aignx Edwin D. de Jong Han1Mar jonahkoemen benetti-a Lorenz Linhardt |
| contents | <p>PathoROB is up and running! With PathoROB, you can:</p> <ul> <li>Measure the robustness of your pathology foundation to model and compare it to 20 state-of-the-art models.</li> <li>Analyze robustness in representation space (robustness index) as well as robustness in downstream applications (classification, clustering).</li> <li>Build more robust foundation models through robustness-aware pre-training or finetuning.</li> <li>Develop new robustification methods that improve robustness without expensive FM re-training.</li> </ul> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18961604 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | bifold-pathomics/PathoROB: v0.0.1 Julius Hense beatriz-aignx Edwin D. de Jong Han1Mar jonahkoemen benetti-a Lorenz Linhardt <p>PathoROB is up and running! With PathoROB, you can:</p> <ul> <li>Measure the robustness of your pathology foundation to model and compare it to 20 state-of-the-art models.</li> <li>Analyze robustness in representation space (robustness index) as well as robustness in downstream applications (classification, clustering).</li> <li>Build more robust foundation models through robustness-aware pre-training or finetuning.</li> <li>Develop new robustification methods that improve robustness without expensive FM re-training.</li> </ul> |
| title | bifold-pathomics/PathoROB: v0.0.1 |
| url | https://doi.org/10.5281/zenodo.18961604 |