Talks on topics related to #automl. Part of the @ELLISforEurope Units Berlin and Freiburg. Past talks: youtube.com/channel/UC3NoO2L…

Joined March 2022
54 Photos and videos
This week Difan Deng will present his ICML 2026 paper on Neural Attention Search at the AutoML Seminar! 🚀 📅 June 18 · 3:00 PM CET 🔗 Details: automl-seminars.github.io/sc…

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🚀Do you want to know how to make your tabular foundation model faster and more scalable? Join our next AutoML Seminar talk by @DHolzmueller about their recent TabICLv2 model! 📅 June 11 · 4 PM CET 🔗automl-seminars.github.io/

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🚀 Next #AutoML Seminar 📅 May 28 · 3PM CET 🎤 Pieter Gijsbers 🧠 OpenML — Past, Present, Future A look back at OpenML’s impact on AI research — and what comes next for open, collaborative AutoML. 🔗 automl-seminars.github.io/sc…

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🚀 Next #AutoML Seminar talk 📅 May 21 · 3PM CET 🎤 Taeyoung Yun 🧠 Posterior Inference in Generative Models for High-dimensional Black-box Optimization 🔗 automl-seminars.github.io/sc…

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🚀Next talk at the AutoML Seminar — Feb 5 · 2:00 PM CET! @solitarypenman: Chronos-2: From Univariate to Universal Forecasting 🔗automl-seminars.github.io/sc…

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🚀 First #AutoML Seminar of 2026! 📅 Jan 15 · 3:00 PM CET 🎤 Andrei Paleyes: Stop Guessing, Start Discovering Trade-offs in Your ML Models 🔗 automl-seminars.github.io/sc…

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🎥 Our latest AutoML Seminar talk is now online! @RobertTLange presents the latest work from @SakanaAILabs: “ShinkaEvolve: Towards Open-Ended and Sample-Efficient Program Evolution.” 👉 Watch here: youtu.be/dAOIer_1INo?si=eO04…
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🎙️ Last talk of the year by @RobertTLange : "ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution" Thursday Dec 11 3pm CET 🔗 Details: automl-seminars.github.io/sc…

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🚀 Next talk at the AutoML Seminar: @j_golebiowski will present: “AutoML without data: training small models with 10 examples” 💡
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🎥 Just dropped! @TomeEftimov on “Benchmarking Beyond Statistics” showing how instance selection algorithmic footprints bring explainability to black-box optimization. Check it out 👇
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🚀 Coming up Nov 20 @ 3 PM CET — @TomeEftimov' talk at the #AutoML Seminar! Tome will talk about "Benchmarking Beyond Statistics: Data-Driven Footprints for Explainable Black-Box Optimization"
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more details here: automl-seminars.github.io/

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🧠 Next talk Oct 30 · 3:00 PM CET — @JakeMRobertson & @Arik_Reuter: Do-PFN: In-Context Learning for Causal Effect Estimation. Explore PFNs for causal estimation from observational tabular data. 🔗 automl-seminars.github.io/sc…

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