Sample-efficient active learning for materials informatics using integrated posterior variance

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Update (Feb 27, 2026): Simon Willison pointed out that WASM support for interpreted languages is further along than I what I thought. wasm32-unknown-wasip1 is a Tier 2 supported target for CPython (meaning failures block releases), with unofficial WASI builds available. Pyodide ports CPython to WASM via Emscripten with support for packages like NumPy, pandas, and SciPy. On the JavaScript side, QuickJS compiled to WASM works well for sandboxed JS execution. Wasmer can run Python server-side on WASM including native modules like gevent and SQLAlchemy. I haven’t tried these yet, but I am looking forward to .

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