Kai's Projects
Class repository for AM205 (Advanced Scientific Computing: Numerical Methods), Fall 2014 at Harvard
๐งโ๐ซ 60 Implementations/tutorials of deep learning papers with side-by-side notes ๐; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), ๐ฎ reinforcement learning (ppo, dqn), capsnet, distillation, ... ๐ง
An R-Java Bayesian Additive Regression Trees implementation
Bayesian Data Analysis demos for Python
Working repository for Causal Tree and extensions
Causal Effect Inference with Deep Latent-Variable Models
Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"
Course notes for CS228: Probabilistic Graphical Models.
The programming assignments from CS228T offered in Spring 2012 at Stanford
An interactive deep learning book with code, math, and discussions, based on the NumPy interface.
Deep Learning Examples
Deep Learning Tutorial notes and code. See the wiki for more info.
predict prob of psychiatric disorders using drug expression profile
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Python version of Factored Spectrally Transformed Linear Mixed Models
Config files for my GitHub profile.
Learning to Learn in TensorFlow
LibRec: A Leading Java Library for Recommender Systems, see
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some commonly used Linux shell commands
programs for MIT6.00.2x
Models and examples built with TensorFlow
Pattern recognition and machine learning toolbox
Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real-world datasets.