Feb. 12, 2024, 5:42 a.m. | Jarrod Mau Kevin Moon

cs.LG updates on arXiv.org arxiv.org

Time series analysis is relevant in various disciplines such as physics, biology, chemistry, and finance. In this paper, we present a novel neural network architecture that integrates elements from ResNet structures, while introducing the innovative incorporation of the Taylor series framework. This approach demonstrates notable enhancements in test accuracy across many of the baseline datasets investigated. Furthermore, we extend our method to incorporate a recursive step, which leads to even further improvements in test accuracy. Our findings underscore the potential …

analysis architecture biology chemistry cs.lg finance framework network network architecture networks neural network neural networks novel paper physics prediction recursive resnet series taylor time series

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