The divergence of ASIC designs makes it difficult to run commonly used modern sequencing analysis pipelines due to software ...

This valuable study introduces a self-supervised machine learning method to classify C. elegans postures and behaviors directly from video data, offering an alternative to the skeleton-based ...

Current methods often overlook the impact of context-dependent sequential text with graph neural networks, leading to an inadequate semantic representation of the text. In this paper, we propose a ...

Abstract: Time-frequency (T-F) domain methods for monaural speech enhancement have benefited from the success of deep learning. Recently, focus has been put on designing two-stream network models to ...

Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne ...

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained ...