Talks on topics related to #automl. Part of the @ELLISforEurope Units Berlin and Freiburg. Past talks: https://xitter.cf/t.co/viEMm3CweJ
Joined March 2022
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🚀 Tabular foundation models, such as TabPFN achieve remarkable performance, but how do they actually make predictions? Join us for the next AutoML Seminar talk by Amir Rezaei Balef on July 16, 3pm CEST
🔗 More details: automl-seminars.github.io/sc…
In case you missed @DHolzmueller talk on TabICLv2, it's now online on our AutoML Seminar YT channel! 🥳
👉youtu.be/MvEkj7TOmj8
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…
🚀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/
🚀 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…
🚀 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…
🎥 The latest AutoML Seminar talk by @solitarypenman on Chronos-2 is now online!
👉 Watch the full talk here: youtube.com/watch?v=wSc76uFp…
🚀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…
🎥 Andrei Paleyes's AutoML Seminar talk on multi-objective optimization to tune your ML models is now online! youtu.be/v-BKxthhrHA?si=UpV7…
🚀 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…
🎥 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…
🎙️ 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…
🎥 New #AutoML Seminar talk is online!
@j_golebiowski — “AutoML without Data: Training Small Models with 10 Examples.”
Watch here 👇
youtube.com/watch?v=ytlZHxRk…
🚀 Next talk at the AutoML Seminar: @j_golebiowski will present: “AutoML without data: training small models with 10 examples” 💡
🎥 Just dropped!
@TomeEftimov on “Benchmarking Beyond Statistics” showing how instance selection + algorithmic footprints bring explainability to black-box optimization.
Check it out 👇
🚀 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"
🧠 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…