4 citations · 5 across the 4 of their papers we have counts for
4 papers
The Syntax and Semantics of einsum
Maurice Wenig, Paul G. Rump, Mark Blacher +1
In 2011, einsum was introduced to NumPy as a practical and convenient notation for tensor expressions in machine learning, quantum circuit simulation, and other fields. It has sinc…
Optimizing Tensor Contraction Paths: A Greedy Algorithm Approach With Improved Cost Functions
Sheela Orgler, Mark Blacher
Finding efficient tensor contraction paths is essential for a wide range of problems, including model counting, quantum circuits, graph problems, and language models. There exist s…
Vectorized and performance-portable Quicksort
Mark Blacher, Joachim Giesen, Peter Sanders +1
Recent works showed that implementations of Quicksort using vector CPU instructions can outperform the non-vectorized algorithms in widespread use. However, these implementations a…
Optimization for Classical Machine Learning Problems on the GPU
Sören Laue, Mark Blacher, Joachim Giesen
Constrained optimization problems arise frequently in classical machine learning. There exist frameworks addressing constrained optimization, for instance, CVXPY and GENO. However,…