On SWE-Bench Verified, the model achieved a score of 70.6%. This performance is notably competitive when placed alongside ...

Abstract: Sparse arrays offer economic advantages by reducing the number of antennas. However, directly utilizing the covariance matrix of sparse array signals for wideband beamforming may lead to the ...

If folks have libraries who are using SciPy sparse matrices, and you'd like help converting them to run/work with sparse array, this sounds like a nice opportunity to work that out. I wrote a ...

ABSTRACT: Node renumbering is an important step in the solution of sparse systems of equations. It aims to reduce the bandwidth and profile of the matrix. This allows for the speeding up of the ...

The test suite in conda-forge/arrow-cpp-feedstock#1664 has a single test failure ===== FAILURES ===== _____ test_sparse_coo_tensor_scipy_roundtrip[f2-arrow_type8 ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.

A new technical paper titled “Signal processing architecture for a trustworthy 77GHz MIMO Radar” was published by researchers at Fraunhofer FHR, Ruhr University Bochum, and Wavesense Dresden GmbH.