Call for Papers Special Issue on Neural networks Depicted in ODEs with Applications  

出　　处：《Tsinghua Science and Technology》2024年第4期1248-1248,共1页清华大学学报自然科学版（英文版）

摘　　要：With the exponential growth in data availability and the advancements in computing power,the importance of neural networks lies in its ability to process large-scale data,enable automation tasks,support decision-making,etc.The transformative power of neural networks has the potential to reshape industries,improve lives,and contribute to the advancement of society as a whole.Neural networks depicted in ordinary differential equations(ODEs)ingeniously integrate neural networks and differential equations,two prominent modeling approaches widely applied in various fields such as chemistry,physics,engineering,and economics.Serving as equations that describe the relationship between a class of functions and their derivatives,ODEs possess rich mathematical analysis methods and are thus integral tools in classical mathematical theory.

关 键 词：theory. ordinary EXPONENTIAL 

分 类 号：O157.5[理学—数学] TP183[理学—基础数学]