Pinned Repositories
Multi-Net
Multi-Net strategy for PINN and its variants
ComputerArchitectureLab
This repository is used to release the Labs of Computer Architecture Course from USTC
cppcheck
static analysis of C/C++ code
documentation
Kata Containers documentation
LabelFree-DNN-Surrogate
Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning
ncc
Neural Code Comprehension: A Learnable Representation of Code Semantics
PhyCRNet
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
phygeonet
PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain
PhySR
Physics-informed deep super-resolution of spatiotemporal data
PINNs
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
lijianfeng97's Repositories
lijianfeng97/PhySR
Physics-informed deep super-resolution of spatiotemporal data
lijianfeng97/PhyCRNet
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
lijianfeng97/Multi-Net
Multi-Net strategy for PINN and its variants
lijianfeng97/space_time_pde
MeshfreeFlowNet: Physical Constrained Space Time Super-Resolution
lijianfeng97/phygeonet
PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain
lijianfeng97/cppcheck
static analysis of C/C++ code
lijianfeng97/PPINN
Demo code for PPINN paper: https://www.sciencedirect.com/science/article/pii/S0045782520304357
lijianfeng97/Question-Independent-Automated-Code-Analysis-and-Grading-using-Bag-of-Words-and-Machine-Learning
Our first hand experience with the recruiting process of companies helped us realize that existing systems judge coding responses solely on the basis of test cases passed and often additional manual involvement is needed to determine the quality of code. We aim to build an open source code base to automatically grade coding responses. This work will help save the tedious effort on the part of Subject Matter Experts (SMEs) by proving useful for grading responses in MOOCs (Massive Open Online Courses) as well as coding rounds in the recruitment process. We have built our work on foundations introduced in extant research in the area. We have achieved better precision (89\%) in addition to better Pearson Correlation Coefficient (0.981) as compared to existing methods by using bag of words technique to calculate the distance vector. Various machine learning models were explored to achieve optimal results. These results and observations provide promise of successful application of this technique in other areas requiring automated grading.
lijianfeng97/PINNs
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
lijianfeng97/LabelFree-DNN-Surrogate
Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning
lijianfeng97/ncc
Neural Code Comprehension: A Learnable Representation of Code Semantics
lijianfeng97/UQPINNs
lijianfeng97/ComputerArchitectureLab
This repository is used to release the Labs of Computer Architecture Course from USTC
lijianfeng97/stopwords
中文常用停用词表（哈工大停用词表、百度停用词表等）
lijianfeng97/documentation
Kata Containers documentation
lijianfeng97/pyc-cfg
Pyc-cfg is a pure python control flow graph builder for almost all Ansi C programming language.