ABSTRACT: We study a non-mixture cure model with a covariate change-point for right-censored survival data and develop maximum-likelihood estimation under a smoothed likelihood to handle the ...
Abstract: We introduce a new method which, for a single noisy time series, provides unsupervised filtering, state space reconstruction, efficient learning of the unknown governing multivariate ...
Abstract: In this paper, using the concept of horizontal membership functions, a new definition of fuzzy derivative called granular derivative is proposed based on granular difference. Moreover, a new ...
A. Cicone, H. Zhou. 'Numerical Analysis for Iterative Filtering with New Efficient Implementations Based on FFT'. Numerische Mathematik, 147 (1), pages 1-28, 2021 ...
If you find this repo useful, please cite our paper. @inproceedings{yi2023fouriergnn, title={Fourier{GNN}: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective}, author={Kun ...
Introduction: Recently, the integration of deep learning techniques and computational materials science has catalyzed significant advances in the microstructural analysis of materials, particularly ...
This three-year degree programme is focused on mathematical and statistical approaches for quantitative management. Mathematics and statistics are core to most modern-day science and have important ...
In recent years, the use of machine learning (ML) in computational chemistry has enabled numerous advances previously out of reach due to the computational complexity of traditional ...
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