A library for easy and efficient manipulation of tensor networks.
Role in this project:
Back-end Developer Contributions:64 reviews, 50 commits, 74 PRs in 3 months
Contributions summary:Adam primarily contributed to the back-end functionality of the tensornetwork library. Their work involved adding and modifying code related to linear algebra operations within the library, specifically focusing on implementing GMRES and other related methods. Furthermore, the user was involved in testing these methods across various backends, including NumPy, JAX, PyTorch, and TensorFlow, ensuring consistent functionality. Additionally, the user added support for new features like pivot, abs, sign, and diagflat.
tensortensor-networksmatrix-product-states
Contributions:26 commits, 21 pushes, 1 branch in 17 days