Abstract: This letter proposes a sampled-data, measurement-robust, risk-aware control barrier function (RA-CBF) framework for stochastic systems with measurement uncertainty. In this framework, what ...
Abstract: This paper compares the performance of activation function hardware under exponential function approximation techniques. The activation function is a key component of deep neural networks, ...
ABSTRACT: Machine learning (ML) has become an increasingly central component of high-energy physics (HEP), providing computational frameworks to address the growing complexity of theoretical ...
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