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Hasktorch is a powerful Haskell library for tensor computation and neural network modeling, built on top of libtorch (the backend of PyTorch). It brings differentiable programming, automatic differentiation, and efficient tensor operations into Haskell’s strongly typed functional paradigm. This project is in active development, so expect changes to the library API as it evolves. We would like to invite new users to join our Hasktorch discord space for questions and discussions. Contributions/PR are encouraged. Hasktorch is a library for tensors and neural networks in Haskell. It is an independent open source community project which leverages the core C++ libraries shared by PyTorch.

...Its design encourages small, reusable building blocks that compose cleanly, while still permitting low-level control where performance matters. The implementation targets efficient compiled code and investigates how advanced type systems can improve reliability in a stack-based language. As a research project, Kitten serves both as a language to experiment with and as a vehicle for ideas about safety and structure in concatenative programming.