Posts

A Gentle Introduction to Deep Sets and Neural Processes

In this post, I will discuss two topics that I have been thinking a lot about recently: Deep Sets and Neural Processes. I'll lay out …

A Brief, High-Level Intro to Amortized VI

In this post I will give a very high-level introduction to the concept of amortized vartiational inference1. Before diving in, let me …

On Model-Based vs. Model-Free AI

An interesting debate has arisen lately in the machine learning community concerning two competing (?) approaches to ML and (more …

Recent Advances in Few-Shot Learning

Few-shot learning is (in my opinion) one of the most interesting and important research areas in ML. It touches at the very core of …

What is a Bayesian Neural Network?

A Bayesian neural network (BNN) refers to extending standard networks by treating the weights as random variables. Thus, training a BNN …

Training Deep Models with Stochastic Backpropagation

Recently I've had to train a few deep generative models with stochastic backpropagation. I've been working with variational …