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    Andrej Risteski Announces CMU Course on AI for Scientific Computing

    The course covers learned surrogates for PDE solving, forecasting, and sampling.

    AR
    3 Sources, 27d ago, first seen 27d ago

    TLDR

    Andrej Risteski, Associate Professor in the Machine Learning Department at CMU, posted that he is teaching 10-749 AI for Scientific Computing in Fall 2026. Each module will include mathematical foundations of classical methods, ML methodology foundations and tricks, and benchmarks plus industry deployment details where public information exists. The syllabus is posted at andrejristeski.github.io/10749F26. Risteski stated he chose the title deliberately to avoid the broader term AI for science, which covers topics such as agentic workflows that the course will not address.

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    3 Sources, first seen 27d ago

    Combined views

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    3 Sources, first seen 27d ago

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    6 comments
    331 saves
    44 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    3 Sources

    @risteski_aThe course isn't named "AI for science" intentionally --- this is a catch-all-term that means different things to different people. In particular, I don't intend to spend much/any time on agentic workflows / automated AI scientists etc. (see reasons in slide below)

    3 Sources

    @risteski_aThe course isn't named "AI for science" intentionally --- this is a catch-all-term that means different things to different people. In particular, I don't intend to spend much/any time on agentic workflows / automated AI scientists etc. (see reasons in slide below)