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Group work and discussion help to build student confidence using math in science lessons, study shows
Group work and giving students time to discuss their work helps to build their confidence in using math in science lessons, a ...
Brain stimulation can boost math learning in people with weaker neural connections
The strength of certain neural connections can predict how well someone can learn math, and mildly electrically stimulating ...
GitHub3d
Learning data-driven discretizations for partial differential equations - GitHub
Code associated with the paper: Learning data-driven discretizations for partial differential equations. Yohai Bar-Sinai, Stephan Hoyer, Jason Hickey, Michael P. Brenner. Proceedings of the National ...
ABS-CBN on MSN14d
From PISAY to the Ivy League: Filipino student graduates from Yale University with double degree
Ariston left a message for other young Filipinos with similar aspirations: “Believe in yourself. Self-doubt is the biggest enemy. And having someone believe in you makes all the difference.” ...
C&EN2mon
Modeling Chemical Reaction Networks Using Neural Ordinary Differential Equations
The dynamic behavior of networks of chemical reactions is typically described using a system of ordinary differential equations (ODEs). Such systems of ODEs are derived by combining the chemical ...
Scientific Research Publishing8mon
Raissi, M. (2018) Deep Hidden Physics Models: Deep Learning of Non-Linear Partial Differential Equations. Journal of Machine Learning Research, 19, 1-24.
Article citations More>> Raissi, M. (2018) Deep Hidden Physics Models: Deep Learning of Non-Linear Partial Differential Equations. Journal of Machine Learning Research, 19, 1-24. has been cited by the ...
marktechpost9mon
Evaluating the Efficacy of Machine Learning in Solving Partial Differential Equations: Addressing Weak Baselines and Reporting Biases
Machine Learning ML offers significant potential for accelerating the solution of partial differential equations (PDEs), a critical area in computational physics. The aim is to generate accurate PDE ...
IEEE9mon
MINN: Learning the Dynamics of Differential-Algebraic Equations and Application to Battery Modeling - IEEE Xplore
The concept of integrating physics-based and data-driven approaches has become popular for modeling sustainable energy systems. However, the existing literature mainly focuses on the data-driven ...
Scientific American1y
These Are the Most Beautiful Equations in Mathematics | Scientific American
Some equations are beautiful because they reveal unexpected relationships between different subjects. The Loewner differential equation, introduced by Charles Loewner in 1923, describes the time ...
Microsoft1y
LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data
Neural operators, as a powerful approximation to the non-linear operators between infinite-dimensional function spaces, have proved to be promising in accelerating the solution of partial differential ...
GitHub1y
Applied Stochastic Differential Equations - GitHub
The book Applied Stochastic Differential Equations gives a gentle introduction to stochastic differential equations (SDEs). The low learning curve only assumes prior knowledge of ordinary differential ...