HeyJaredMindful Modeler
Better machine learning by thinking like a statistician. About model interpretation, paying attention to data, and always staying critical.
- Indexed issues, last 90 days
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- Jul 22, 2026
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- Jul 7, 2026
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Trends in tabular foundation research (opens the original)
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151 papers on tabular and time series foundation models were presented at “Foundation Models for Structured Data”, a workshop that took place for the second time at ICML this month in Seoul.I didn’t attend, but still marked the event in my calendar to check on current trends in tabular foundation research. Going through the titles and some abstracts was very informative, and I want to share my observations about the state of tabular foundation research.If you are new to tabular foundation models
Time for a change (opens the original)
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Sometimes you have to make a big change in life. You’ve probably been there yourself.For me, this time is now.In 2022, I made the scary decision to become self-employed as a writer for technical books. With the Interpretable ML book already under my belt, some financial runway, and a support network, I gave it a try. I didn’t want to look back at my life and regret never trying the author life. There was a real risk, since most authors can’t live from writing books. Fortunately, I managed to mak
TabFM minus the hype (opens the original)
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Google Research published TabFM, a new tabular foundation model.The AI influencers found out, and social media is now awash in TabFM posts.Let’s talk about what TabFM is and isn’t, without the hype.TabFM is a tabular foundation model with in-context learningTabFM is a tabular foundation model like TabPFN, TabICL, and TabDPT.More technically, TabFM is a transformer-based neural network pre-trained on hundreds of millions of synthetic datasets. TabFM makes predictions via in-context learning: ther
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