End-to-End Acoustic Modeling using Convolutional Neural Networks for HMM-based Automatic Speech Recognition

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The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

Many feedforward neural networks (NNs) generate continuous and piecewise-linear (CPWL) mappings. Specifically, they partition the input domain into regions on which the mapping is affine. The number of these so-called linear regions offers a natural metric ...

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The Lizorkin space is well suited to the study of operators like fractional Laplacians and the Radon transform. In this paper, we show that the space is unfortunately not complemented in the Schwartz space. In return, we show that it is dense in C0(Double- ...

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End-to-End Acoustic Modeling using Convolutional Neural Networks for HMM-based Automatic Speech Recognition

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Partial discharge localization in power transformer tanks using machine learning methods

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Explicit representations for Banach subspaces of Lizorkin distributions

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