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> I think it's better to think of JAX as a more general framework for differentiable programming and PyTorch more focused specifically on deep learning/neural
by jstx1 4y ago
> I think it's better to think of JAX as a more general framework for differentiable programming and PyTorch more focused specifically on deep learning/neural networks.
I don't get the point of this distinction - JAX was developed specifically for ML. What else is it being used for right now?
- geysersam 4y agoMy impression is that people are experimenting more with automatic differentiation for more traditional scientific computing applications. Although, I've mainly heard about Julia in that context, not Jax.
- PartiallyTyped 4y agoI have used it for a numerical optimisation library that I wrote as part of a class. It’s probably also useful in population and metaheuristic scenarios where the optimisation objective can be described mathematically, allowing you to make use of GPGPUs, and if possible first and second order derivatives.