hejiandong (Hejiandong)

Hejiandong

Geek Repo

Company:Beijing Institute of Technology

Location:Beijing, China

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hejiandong's repositories

airfoil-opt-gan

Experiment code associated with our paper: "Aerodynamic Design Optimization and Shape Exploration using Generative Adversarial Networks"

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ASTGCN

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN) AAAI 2019

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ASTIR

Citywide Crowd Flow Prediction

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Deep-Flow-Prediction

A framework for fluid flow (Reynolds-averaged Navier Stokes) predictions with deep learning

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DeepCFD

DeepCFD: Efficient Steady-State Laminar Flow Approximation with Deep Convolutional Neural Networks

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deepflame-dev

A deep learning empowered open-source platform for reacting flow simulations

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DeepVIV

Deep Learning of Vortex Induced Vibrations

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Dynamic-Morphing-Wing

This project contains the user-defined functions (UDF) necessary to perform unsteady computational fluid dynamics (CFD) analysis of dynamically morphing wings equipped with morphing flaps.

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eat_tensorflow2_in_30_days

Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

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finitevolume-python

Finite Volume simulation of the Kelvin-Helmholtz Instability

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FVENS

Finite volume Euler / Navier-Stokes solver

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GCN-tffc

比较 TCN、GRU、GCN、TGCN、 TCN+GCN 在 交通流量预测方面的准确率效果。

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GCN_predict-Pytorch

Traffic flow predict. Implementation of graph convolutional network with PyTorch

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Graph_Convolutional_LSTM

Traffic Graph Convolutional Recurrent Neural Network

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lily-pad

Real-time two-dimensional fluid dynamics simulations in Processing. Initiated by Dr G D Weymouth:

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Physics-Informed-Deep-Learning-Solid-and-Fluid-Mechanics

Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube problems and plane stress linear elasticity boundary value problems

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PINN-in-Pytorch

Implementation of PINN from Raissi in Pytorch

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PINN-laminar-flow

Physics-informed neural network for solving fluid dynamics problems

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pinn_cavity

Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.

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PINNs

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

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PINNs-TF2.4.0

Contains implementation of PINN using Tensorflow 2.4.0

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PointNetCFD

Point-cloud deep learning for prediction of fluid flow fields on irregular geometries (supervised learning)

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PyDMD

Python Dynamic Mode Decomposition

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PythonRobotics

Python sample codes for robotics algorithms.

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SeismicMesh

2D/3D serial and parallel triangular mesh generation tool for finite element methods.

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Self-Driving-Truck

Self-driving smallscale truck with wireless charging - Master thesis @ NTNU 2019

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space_time_pde

MeshfreeFlowNet: Physical Constrained Space Time Super-Resolution

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T-GCN

Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method

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ToGCN-V2X

The official implementation of the paper "Topological Graph Convolutional Network-Based Urban Traffic Flow and Density Prediction"

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tvmathew1986-Physics_Informed_Neural_Network_for_Continuum_Mechanics_application

The repository contains implementations of examples provided in the literature on energy minimization based approach to Physics Informed Neural Network implementation in Tensorflow using Jupyter notebooks.

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