R package for score matching by automatic differentiation
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Updated
Jun 13, 2024 - C++
R package for score matching by automatic differentiation
A JIT compiler for hybrid quantum programs in PennyLane
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Julia bindings for the Enzyme automatic differentiator
Tensor library for machine learning
Automates adjoints. Forward and reverse mode algorithmic differentiation around implicit functions (not propagating AD through), as well as custom rules to allow for mixed-mode AD or calling external (non-AD compatible) functions within an AD chain.
Automatic differentiation of implicit functions
PotentialLearning.jl: Composable Optimization Workflows for Fast and Accurate Interatomic Potentials.
High-performance automatic differentiation of LLVM and MLIR.
A differentiable physics engine and multibody dynamics library for control and robot learning.
Comprehensive automatic differentiation in C++
adam implements a collection of algorithms for calculating rigid-body dynamics in Jax, CasADi, PyTorch, and Numpy.
A Julia interface to the C++ library ColPack for graph and sparse matrix coloring.
A minimal OpenCL, CUDA, Vulkan and host CPU array manipulation engine / framework.
JAX compilation of RDDL description files, and a differentiable planner in JAX.
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
A numerical and automatic mathematical library in C++ for scientific and graphical applications.
Julia interface to the Generalised Truncated Power Series Algebra (GTPSA) library
⟨Grassmann-Clifford-Hodge⟩ multilinear differential geometric algebra
An interface to various automatic differentiation backends in Julia.
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