Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowl
data sets, deep learning has transformed fields such as computer vision and natural language processing. Now, it is becoming the method of choice for many genomics modelling tasks, including predicting the impact of genetic variation on gene regulatory mechanisms such as DNA accessibility and splicing...
Since the deep learning is now a hot topic in computational mechanics with neural networks and many related studies have been reported recently, we discuss here some features of computational mechanics with deep learning. First, similarity and difference
A DNA-based storage system for biomedical images is proposed, combining compression, error correction and deep learning repair. It achieves 97.20% image quality at 7× coverage depth, demonstrating high compression and fault tolerance. Guanjin Qu ...
The advent of artificial intelligence (AI) in architecture - the first genuine 21st-century design method - is changing the way buildings are imagined and designed. AI image generators like Midjourney and DALL-E provide an efficient and explorative way of conceiving architectural concepts. Generated...
第一篇是2016年Molecular System Biology的文章,题目是Deep learning for computational biology,题目很大,但是它主要只讲了调控基因组(regulatory genomics)和生物图像分析两部分内容。正巧,第二篇是即将在Bioinformatics见刊的文章,题目是An introduction to deep learning on biological sequence data -- examples and ...
The first example is designed to show that HiDeNN is capable of achieving better accuracy than conventional finite element method by learning the optimal nodal positions and capturing the stress concentration with a coarse mesh. The second example applies HiDeNN for multiscale analysis with sub-...
FLOPs (Floating Point Operations) and MACs (Multiply-Accumulate Operations) are metrics that are commonly used to calculate the computational complexity of deep learning models. They are a fast and easy way to understand the number of arithmetic operations required to perform a given computation. Fo...
E. (2021). DeepXDE: A deep learning library for solving differential equations. SIAM Review, 63(1), 208–228. Article Google Scholar Malek, A., & Beidokhti, R. (2006). Numerical solution for high order differential equations using a hybrid neural network-optimization method. Applied ...
本文使用深度神经网络完成计算蛋白质设计去预测20种氨基酸概率。 Introduction 针对特定结构和功能的蛋白质进行工程和设计,不仅加深了对蛋白质序列结构关系的理解,而且在化学、生物学和医学等领域都有广泛的应用。在过去的三十年里,蛋白质设计取得了显著的成功,其中一些