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A machine learning model to learn the numerical solution of 2 dimensional Backward Facing Step.An Artificial Neural Network (ANN) architecture is developed which can learn the spatial and temporal …
A python code for solving flow across 2 dimensional backward facing step.
[IJCAI'18] Spatio-Temporal Graph Convolutional Networks
Implementation of Diffusion Convolutional Recurrent Neural Network in Tensorflow
The official code for "Spatial temporal transformer networks for traffic flow forecasting"
This is a PyTorch implementation of STGAGRTN in the Spatial-Temporal Graph Attention Gated Recurrent Transformer Network for Traffic Flow Forecasting.
Imposition of Hard Convex Constraints on Neural Networks
Python code for solving Napier Stokes equation using finite volume method in the scenario of Lid driven flow. The quasi Rhie Chow algorithm has been implemented to arrive at the solution.
十二种主题风格 - Material Google JetBrains Vue Juejin Purple Ayu Dark
Parametric Gaussian Process Regression for Big Data (Matlab Version)
Machine learning of linear differential equations using Gaussian processes
Deep Learning of Turbulent Scalar Mixing
Parametric Gaussian Process Regression for Big Data
Hidden physics models: Machine learning of nonlinear partial differential equations
Tutorial on a number of topics in Deep Learning
Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations
Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
Applied Mathematics (APPM) Department Colloquium
Introduction to Machine Learning in R
✅ Curated list of resources for college students