A note on joint model

https://rpubs.com/enwuliu/1449608 

Understanding the Joint Model Likelihood

https://rpubs.com/enwuliu/1447741 

MCMC and Unnormalized Posterior

https://rpubs.com/enwuliu/1446775 

highest posterior density (HPD)

 https://rpubs.com/enwuliu/1446293

Complete steps of the Bayesian Hierarchical Normal Model

https://rpubs.com/enwuliu/1446203 

SAR and CAR models

https://rpubs.com/enwuliu/1445777 

Spatial variogram analysis

https://rpubs.com/enwuliu/1444788 

Spatial-Temporal Interaction Models in INLA

https://rpubs.com/enwuliu/1444036 

Understanding SPDE approach

https://rpubs.com/enwuliu/1443568

The SPDE Approach: From Gaussian Fields to GMRFs

 https://rpubs.com/enwuliu/1443160

Derivation of the Posterior Predictive Distribution

 https://rpubs.com/enwuliu/1442659

Understanding INLA: A Step-by-Step Implementation Note

https://rpubs.com/enwuliu/1441980 

Metropolis-Hastings Algorithm: A Complete Review

https://rpubs.com/enwuliu/1441487 

Full Conditional Distributions and Gibbs sampling

https://rpubs.com/enwuliu/1439251 

Spatio-temporal modeling of particulate matter concentration through the SPDE approach

 Just a note,

https://rpubs.com/enwuliu/1429888

Understanding SIFT Features in computer vision

https://rpubs.com/enwuliu/1341167 

This is the paper which is not difficult to understand https://link.springer.com/article/10.1023/B:VISI.0000029664.99615.94

A multimodal deep learning model for knee osteoporosis diagnosis

https://huggingface.co/spaces/enwuliu/ko 

A simple deep learning application for classifying images of cats and dogs

https://huggingface.co/spaces/maogo123/maogo

Another one using PyTorch.

https://huggingface.co/spaces/maogo123/cat-dog-classifier

Mathematical Intuition: Why the Gradient Points Toward Increasing Loss

 https://rpubs.com/enwuliu/1325892

Understanding Entropy in Machine Learning

https://rpubs.com/enwuliu/1325285