Fiona K. Ewald

#Girls’Day2026: On April 23, 2026, the #MCML, together with Deep Tech Collective and CreAITech , invites girls aged 14–16 to an interactive Girls’ Day at the Hochschule für Philosophie München.

💡 Find out more: www.girls-day.de/.oO/Show/mun...

#ki #artificialintelligence #münchen #beratung #startup | Tailor-made AI Consulting Wir haben den Schritt gewagt. 🚀 Wir haben uns dazu entschieden, unsere eigene KI-Beratung zu gründen. Viele Unternehmen sehen das riesige Potenzial von KI – und trotzdem schaffen es die wenigsten, di...

Great news 🚀

www.linkedin.com/posts/tailor...

Great experience presenting my work in progress on #RashomonSets for #interpretability and #performance analysis at MCML Munich AI Day last week!

A fantastic chance to connect, learn, and share ideas - big thanks to the @munichcenterml.bsky.social for organizing.

#AI #MachineLearning #IML #xAI

Thank you so much @daiichisankyo.bsky.social for welcoming me in your office in Munich!

Feature importance measures can clarify or mislead. PFI, LOCO, and SAGE each answer a different question.
Understand how to pick the right tool and avoid spurious conclusions: mcml.ai/news/2025-03...
@fionaewald.bsky.social @ludwig-bothmann.bsky.social @giuseppe88.bsky.social @gunnark.bsky.social

Thank you for sharing! 🙏🏻

The @munichcenterml.bsky.social recently shared our work: mcml.ai/news/2025-03... 🙏🏻

#mcml #ai #interpretability #iml #xAI #blockpost

GitHub - bips-hb/cpi: CPI: Conditional Predictive Impact CPI: Conditional Predictive Impact. Contribute to bips-hb/cpi development by creating an account on GitHub.

I was thinking of using the implementation from the CPI package (github.com/bips-hb/cpi/) by Watson D. S. & Wright, M. N. (2021) "Testing conditional independence in supervised learning algorithms" ML.

Need an implementation of a conditional sampler, as required, e.g., in Conditional Feature Importance, for a project in R. Since I don't think it's efficient for everyone to implement their own, I'll ask around: Do you know a good implementation?

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Would be great if you could add me, too. Thank you!

A Guide to Feature Importance Methods for Scientific Inference While machine learning (ML) models are increasingly used due to their high predictive power, their use in understanding the data-generating process (DGP) is limited. Understanding the DGP requires ins...

Excited to be part of this platform!
My research focuses on global model-agnostic feature importance. Please check our recent paper: "A Guide to Feature Importance Methods for Scientific Inference" (link.springer.com/chapter/10.1...).