AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
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一分钟完成验证JAX-native inference and reconstruction layer of the MIDGARD stack: observables, likelihoods, priors, parameter handling, optimizers, samplers and made-to-measure for differentiable N-body forward models, written against solver protocols rather than any one solver (jaccpot, nornax, ODISSEO). Named for Mímir's well beneath Yggdrasil.
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取自仓库 README
正在加载完整 README。 以下为已保存的摘录。
mimirax is the inference and reconstruction layer of the MIDGARD stack: a JAX-native package
that fits, samples and diagnoses the parameters of differentiable N-body forward models. It
owns observation operators, likelihoods, priors, parameter handling and inference methods, and
it reaches forces and integrators only through protocols — never by importing a solver.查看完整 README ↗目前无法加载完整 README。请通过原文链接阅读。 以下为已保存的摘录。
mimirax is the inference and reconstruction layer of the MIDGARD stack: a JAX-native package
that fits, samples and diagnoses the parameters of differentiable N-body forward models. It
owns observation operators, likelihoods, priors, parameter handling and inference methods, and
it reaches forces and integrators only through protocols — never by importing a solver.查看完整 README ↗