ZEXINLIU
Ph.D. in Computational Math. My research interests are uncertainty quantification applied in biomedical simulation cardiac bioelectricity.
University of UtahSalt Lake City
Pinned Repositories
Deep-learning
Stanford CS231n, Convolutional Neural Networks for Visual Recognition
Machine-Learning
:zap:机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归
Machine-Learning-Session
Derivation of Math in ML via Whiteboard
ML
Multi_ttr_examples
Phase-diagrams
Rwave_detect
R-wave detection
Singular_FPDE
Solve fractional PDE along with singular perturbation problem
Spectrum_reconst
Algorithms for spectrum reconstruction
Uni_ttr_examples
We evaluate the new algorithms, PC and PCL against existing methods in terms of accuracy and efficiency for a range of different measures.
ZEXINLIU's Repositories
ZEXINLIU/Deep-learning
Stanford CS231n, Convolutional Neural Networks for Visual Recognition
ZEXINLIU/Machine-Learning
:zap:机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归
ZEXINLIU/Machine-Learning-Session
Derivation of Math in ML via Whiteboard
ZEXINLIU/ML
ZEXINLIU/Multi_ttr_examples
ZEXINLIU/Phase-diagrams
ZEXINLIU/Rwave_detect
R-wave detection
ZEXINLIU/Singular_FPDE
Solve fractional PDE along with singular perturbation problem
ZEXINLIU/Spectrum_reconst
Algorithms for spectrum reconstruction
ZEXINLIU/Uni_ttr_examples
We evaluate the new algorithms, PC and PCL against existing methods in terms of accuracy and efficiency for a range of different measures.
ZEXINLIU/zexinliu.github.io
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