Zobrazeno 1 - 10
of 519
pro vyhledávání: '"Shao, Qun"'
Identifying gene splicing is a core and significant task confronted in modern collaboration between artificial intelligence and bioinformatics. Past decades have witnessed great efforts on this concern, such as the bio-plausible splicing pattern AT-C
Externí odkaz:
http://arxiv.org/abs/2406.11900
Past decades have witnessed a great interest in the distinction and connection between neural network learning and kernel learning. Recent advancements have made theoretical progress in connecting infinite-wide neural networks and Gaussian processes.
Externí odkaz:
http://arxiv.org/abs/2403.17467
Recent years have witnessed a hot wave of deep neural networks in various domains; however, it is not yet well understood theoretically. A theoretical characterization of deep neural networks should point out their approximation ability and complexit
Externí odkaz:
http://arxiv.org/abs/2210.15279
Recent years have emerged a surge of interest in SNNs owing to their remarkable potential to handle time-dependent and event-driven data. The performance of SNNs hinges not only on selecting an apposite architecture and fine-tuning connection weights
Externí odkaz:
http://arxiv.org/abs/2207.04876
This work aims to provide an effective deep learning framework to predict the vector-soliton solutions of the coupled nonlinear equations and their interactions. The method we propose here is a physics-informed neural network (PINN) combining with th
Externí odkaz:
http://arxiv.org/abs/2205.10230
This study has investigated an artificial intelligence technology ¿ model trees ¿ as a modelling tool applied to an immediate release tablet formulation database. The modelling performance was compared with artificial neural networks that have been
Externí odkaz:
http://hdl.handle.net/10454/3051
This study compares the performance of neurofuzzy logic and neural networks using two software packages (INForm and FormRules) in generating predictive models for a published database for an immediate release tablet formulation. Both approaches were
Externí odkaz:
http://hdl.handle.net/10454/2998
In the pharmaceutical field, current practice in gaining process understanding by data analysis or knowledge discovery has generally focused on dealing with single experimental databases. This limits the level of knowledge extracted in the situation
Externí odkaz:
http://hdl.handle.net/10454/3439
Publikováno v:
In Journal of Molecular Structure 15 December 2024 1318 Part 2
