A Haskell DSL for deep learning models

In plain words

This is a domain-specific language built in Haskell for defining deep neural networks. It allows developers to write network architectures that can be compiled to both Caffe and Torch formats, two popular deep learning frameworks. The tool is designed for researchers and engineers who want to express complex neural network models in a high-level, functional programming style rather than using framework-specific syntax directly.

written from the facts on this page · September 2026

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