Brancher vs CuPy: What are the differences?

Brancher: A Python package for differentiable probabilistic inference. It is a user-centered Python package for differentiable probabilistic inference. It allows to design and train differentiable Bayesian models using stochastic variational inference. It is based on the deep learning framework PyTorch; CuPy: A NumPy-compatible matrix library accelerated by CUDA. It is an open-source matrix library accelerated with NVIDIA CUDA. CuPy provides GPU accelerated computing with Python. It uses CUDA-related libraries including cuBLAS, cuDNN, cuRand, cuSolver, cuSPARSE, cuFFT and NCCL to make full use of the GPU architecture.

Brancher and CuPy can be primarily classified as "Data Science" tools.

Brancher and CuPy are both open source tools. It seems that CuPy with 4.14K GitHub stars and 373 forks on GitHub has more adoption than Brancher with 188 GitHub stars and 30 GitHub forks.