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

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WebAssembly has come a long way since its first release in 2017. The first version of WebAssembly was already a great fit for low-level languages like C and C++, and immediately enabled many new kinds of applications to efficiently target the web.

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With normal Smalltalk code, I would explore the system using senders, implementors, inspectors— gradually rebuilding my understanding. Here, that breaks down. The matching syntax lives inside strings, invisible to standard navigation tools. No code completion. No refactorings. No help from the environment.

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