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Hi there!

  • 📚 This is Zhidi Lin, a PhD student at the School of Science and Engineering, CUHK-Shenzhen

  • 🔬 My current research interests include data-driven modeling (particularly the Bayesian learning and inference), distributed/federated learning

Max's Projects

deep-learning-wizard icon deep-learning-wizard

Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, C++ and more.

dlwpt-code icon dlwpt-code

Code for the book Deep Learning with PyTorch by Eli Stevens and Luca Antiga.

gnnpapers icon gnnpapers

Must-read papers on graph neural networks (GNN)

gpssmtorch icon gpssmtorch

An implementation of GP-SSM inference algorithms using pytorch

kalman-and-bayesian-filters-in-python icon kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

machine-learning-algorithms-matlab icon machine-learning-algorithms-matlab

Contains ML Algorithms implemented as part of CSE 512 - Machine Learning class taken by Fransico Orabona. Implemented Linear Regression using polynomial basis functions, Perceptron, Ridge Regression, SVM Primal, Kernel Ridge Regression, Kernel SVM, Kmeans.

mlbop icon mlbop

Matlab code for S. Theodoridis' "Machine Learning: A Bayesian and Optimization Perspective" (2015).

ssgpr icon ssgpr

Sparse Spectrum Gaussian Process Regression

tgp.pytorch icon tgp.pytorch

Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021

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