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Wir haben eine Stellungnahme zur aktuellen Diskussion um Omikron veröffentlicht. Wir plädieren weiterhin für eine Daten-basierte Steuerung der Pandemie. covid19.statistik.uni-muenchen.de/pdfs/codag-ste…

Teaching a course on #causality in ML for the first time next semester at TU München What resources should I look at (courses, books, topics, examples, talks, papers, ...)? What should I (not) include? Happy about all suggestions!

Marginal Effects for Non-Linear Prediction Functions deepai.org/publication/ma… by Christian A. Scholbeck et al. including Giuseppe Casalicchio #Estimator #Statistics

Imagine a parallel universe in which researchers receive money from the journal that publishes their work. Just like book authors do.

Both global & local explanations have their pros & cons in #MachineLearning (e.g., global can be misleading when features interact). Our framework visualizes regional feature effects as a trade-off between global & local and quantifies feature interactions. #XAI #ML #AI

Looking for an open Ph.D. position in interpretable #MachineLearning at Universität München in SLDS / Bernd Bischl's group? Want to build on the research of Christoph Molnar 🦋 christophmolnar.bsky.social? Apply now: lmu.de/en/about-lmu/w… #interpretableML #iml #ExplainableAI #xai #DataScience

Zotero 6: Your research workflow, transformed zotero.org/blog/zotero-6

Es gibt viele Dinge, die mich hier wütend machen. Auch deshalb bin ich nicht mehr #IchBinHanna 🧵 (1/n) jmwiarda.de/2022/06/27/der…

Winner: data.table::as.data.table(mtcars)[,min(mpg), by="cyl"]

Special track on "Model-agnostic explanations" at the 1st World Conference on eXplainable Artificial Intelligence xaiworldconference.com/accepted-speci… (July 26 - 28, 2023 in Lisbon) with Proceedings in Springer's CCIS. Submission deadline: April 20, 2023 #XAI Explainable AI #ExplainableAI

Excited to announce our new book “Applied Machine Learning Using mlr3 in R”, will be published by Chapman+Hall on 19 Jan. Authored and edited by mlr core team, it provides a practical guide to #MachineLearning in #RStats using our #mlr3 software routledge.com/Applied-Machin…

Passionate about diving into the world of Interpretable Machine Learning and Explainable AI for a PhD at Universität München? Apply now! 🎓 Explainable AI #PhD #XAI #MachineLearning #Statistics #ExplainableAI #DataScience #InterpretableML job-portal.lmu.de/jobposting/09f…

Got data and questions? Get FREE support from data science and statistics students at Universität München! Further information: stablab.stat.uni-muenchen.de/lehre/pdfs/inf… and stablab.stat.uni-muenchen.de/lehre/pdfs/inf… or contact F. Scheipl fda.statistik.uni-muenchen.de/people/head/sc… #Statistics #MachineLearning #rstats #python #DataScience

📜🚨Paper alert! Check out our new preprint on how explaining Bayesian optimization fosters human-AI teamwork. Great collaboration w/ Artificial Intelligence and Machine Learning @ LMU Universität München Munich Center for Machine Learning Harvard University Wyss Institute

NEW accepted ICML'24 position paper: Rethinking Empirical Research in Machine Learning: Addressing Epistemic and Methodological Challenges of Experimentation arxiv.org/abs/2405.02200 Maybe of interest to some here. Anne-Laure Boulesteix Artificial Intelligence and Machine Learning @ LMU Matthias Feurer

We are looking for a PhD in Interpretable Machine Learning and Explainable AI Universität München. Apply now at join.com/companies/uni-…! Explainable AI #PhD #XAI #MachineLearning #Statistics #ExplainableAI #DataScience #InterpretableML

Our #ICLR paper, “Efficient & Accurate Explanation Estimation with Distribution Compression” made the top 5.1% of submissions and was selected as a Spotlight! Congrats to the first author Hubert Baniecki #xAI #interpretableML Paper: arxiv.org/abs/2406.18334

Me: Spent an hour crafting a detailed, thoughtful review in the submission portal. Hit 'Submit'. EasyChair-Portal: You have been logged out. Me: Log back in… everything is gone. EasyChair? More like EasyDespair. I am retiring from reviewing. #ReviewPain #xAI

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/2025-03-2…