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2025-12-17 22:14:18
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Gen Home Documentation Tutorials Source Ecosystem Gen An open-source stack for generative modeling and probabilistic inference Why Gen Gen automates the implementation details of probabilistic inference algorithms Gen’s inference library gives users building blocks for writing efficient probabilistic inference algorithms that are tailored to their models, while automating the tricky math and the low-level implementation details. Gen helps users write hybrid algorithms that combine neural networks, variational inference, sequential Monte Carlo samplers, and Markov chain Monte Carlo. Gen allows users to flexibly navigate performance trade-offs Gen features an easy-to-use modeling language for writing down generative models, inference models, variational families, and proposal distributions using ordinary code. But it also lets users migrate parts of their model or inference algorithm to specialized modeling languages for which it can generate especially fast code...
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