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An open-source stack for generative modeling and probabilistic inference. 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 features an easy-to-use modeling language...

Zygote provides source-to-source automatic differentiation (AD) in Julia, and is the next-gen AD system for the Flux differentiable programming framework. For more details and benchmarks of Zygote's technique, see our paper. You may want to check out Flux for more interesting examples of Zygote usage; the documentation here focuses on internals and advanced AD usage.

... into Flux models. Cutting-edge models such as Neural ODEs are first class, and Zygote enables overhead-free gradients. GPU kernels can be written directly in Julia via CUDA.jl. Flux is uniquely hackable and any part can be tweaked, from GPU code to custom gradients and layers.

This discordbot will be available to all servers who are hosting Risk tournaments, so there is an easy and centralised way to track statistics for players, scores, tournament settings, and much more data that will be nicely output into a userfriendly environment (being plaintext data structured to be viewed in discord-chat, twitch-chat or via a nice designed website.)