Reflecting on “Towards Evaluating the Robustness of Neural Networks”:
A few thoughts about the paper that brought me into the field of adversarial machine learning.
Rapid Iteration in Machine Learning Research:
I wrote a tool to help me quickly iterate on research ideas by snapshoting Python state.
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).