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An Example of Graph Convolutional Networks
Controlled experiments are run on the Citeseer citation graph to understand how GCNs work
Adversarial Validation
How to use Adversarial Validation to diagnose overfitting problems
AdaNet - Adaptive Structural Learning of Artificial Neural Networks
A paper review of Google's AdaNet AutoML technique, which learns the optimal neural network structure
Machine Learning Security
Exploring the vulnerabilities of ML models from attack by bad actors. They're more fragile than you might think
Implementing Git in Data Science
Some thoughts on how to apply version control when conducting experiments
Overview of GANs - Part III
Learning Disentangled Representations: an introduction to InfoGAN
Overview of GANs - Part I
An introduction to Generative Adversarial Networks
Bayesian Additive Regression Trees
A paper review of BART, which is the Bayesian approach to Additive Tree models
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
A paper review on using Random Forests to estimate causal impact