Rust frontend to LuisaCompute and more!

End-to-end differentiable blind tip reconstruction on Colab implemented with PyTorch

Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.

Productive, portable, and performant GPU programming in Python.

👀🔥 Differentiable foveated vision for Deep Learning methods

Deep relational learning through differentiable logic programming.

A general-purpose probabilistic programming system with programmable inference

A differentiable bridge between phase space and Fock space

Julia bindings for the Enzyme automatic differentiator

High-performance automatic differentiation of LLVM and MLIR.

test-bed for differentiable parameter optimization of molecular systems

Compositional Differentiable Programming Library

Differentiable Finite Element Method with JAX

Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes

Differentiable and accelerated spherical transforms with JAX

Differentiable and accelerated wavelet transform on the sphere with JAX

An open source Julia library for active learning of interatomic potentials in atomistic simulations of materials. It incorporates elements of bayesian inference, machine learning, differentiable programming, software composability, and high-performance computing.

Robot kinematics implemented in pytorch

A common interface for quadrature and numerical integration for the SciML scientific machine learning organization

A differentiable programming language with an integration primitive that soundly handles interactions among the derivative, integral, and discontinuities.