A Case of Plagarism in Machine Learning: A recent paper has copied a bunch of text from over a dozen prior papers. This is bad.

Multiplexing Circuits on the Game of Life - Part 5: Wherein I yet again re-design my game of life circuit setup and make things even more efficient.

Research Paper Release Checklist: Steps to take to reduce the likelihood of embarrassing errors when submitting papers, uploading research papers to arXiv, or submitting final camera-ready papers.


A Simple CPU on the Game of Life - Part 4: A full Turing complete Unlimited Register Machine implemented on top of the game of life.

Yet Another MOBA (In 13kb of JavaScript): an online multiplayer game as part of a series on game-development in 13k of JavaScript.

Improved Logic Gates on Conway's Game of Life - Part 3: more efficient digital logic gates constructed on top of the game of life.


Yet Another Space Game (In 13kb of JavaScript): another small pointless game building on my prior doom clone.

InstaHide Disappointingly Wins Bell Labs Prize, 2nd Place: InstaHide, a recent scheme that claims to train neural networks with privacy, is completely broken but was awarded the Bell Labs Prize, 2nd place.

Screen Recording of Breaking a Defense to Adversarial Examples: I broke another defense, but this time recorded my screen the entire (2.5) hour session it took.

An Introduction to Circuit Design on Conway's Game of Life - Part 2: Basic circuit design to build a 7-segment display using the AND/OR/NOT gates built last time.

Digital Logic Gates on Conway's Game of Life - Part 1: Constructing game of life “gadgets” that act as digital logic gates, allowing Turing-complete computation.

Are Adversarial Example Defenses Improving?: A short collection of thoughts after writing a paper where we broke a dozen recent defenses to adversarial examples, again.


Yet Another Doom Clone (In 13kb of JavaScript): exactly what it sounds like; an entry for js13k 2019.

A 3D Shadow Mapping Renderer in JavaScript: because it's possible.

List of All Adversarial Example Papers: a continuously-updating list of all 1000+ papers written on adversarial examples available on arxiv.


Adversarial Machine Learning Reading List: a collection of papers I recommend reading for those interested in studying adversarial machine learning (for the time being, focusing on the sub-field of adversarial examples).

Advice on Evaluating Adversarial Example Defenses: recommendations for how to perform adversarial example defense evaluations (or how to determine if an evaluation in a defense paper is adequate).