Understanding the benefits of matrix converters for EV chargers and a comparison of different matrix converter topologies.
Abstract: Sparse General Matrix-Matrix Multiplication (SpGEMM) is a core operation in high-performance computing applications such as algebraic multigrid solvers, machine learning, and graph ...
Abstract: Moving target detection in a disturbing environment has been significantly active and challenging for underwater acoustic array signal processing. One of the most effective approaches is ...
Sparse Autoencoders (SAEs) have recently gained attention as a means to improve the interpretability and steerability of Large Language Models (LLMs), both of which are essential for AI safety. In ...
Since our sparse attention is implemented by FlexAttention, we recommend conducting a warm-up inference first, as subsequent inferences will perform better in terms of speed. To better demonstrate the ...
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