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This is a collection of useful blogs, websites, and pages aimed at:

My Content

Python and the infinite I made a post on python-dev about Python has some inconsistencies handling math - A programming language and website I built. Also check out the REPL

Useful Apps/Software

Digital Media - A color palette generator - A color palette generator, using mathematical relationships - GauGAN online application that you can sketch and generate great images from very little information

Math/Programming - Online numerical calculator, with arbitrary precision and symbolic computation - Embedded computer vision library

Academic Resources

Tutorials - Using AI to do stock trading



Polyhedral compilation, great for the diagrams and tiling explanation - polyhedral compilation diagrams and tiling

Papers/Releases - DALL-E 2, a hugely impressive leap forward in image synthesis. here’s an article I wrote about it - Interesting research looking at GPT model appplied to web browsers, with citing sources - Chinchilla, better and smaller than GPT-3. Also, this paper has a great introduction that explains broad ideas in ML/AI - AIVC, AI-powered image/video compression - Neural network based text compression - Tensorflow compression models - Generates decent quality videos from text conditioning - Video frame interpolation (really good, use it on all your videos!) - Style transfer model for images - NLP word encoding method - Denoising model for images, useful for Blender rendering and restoring low quality videos - Wikipedia database dumps (I’m working on a personal project with this…)

Datasets - Vimeo90k dataset of high quality videos - Large web text database - Common crawl of the entire web - Sports-1M dataset, scraped from YT



Gregory Croisdale

A frequent collaborator, we’ve worked together on Avocat, CARVE, and many, many, more

Stan Tomov

My research advisor for ~2 years at ICL, who researches linear algebra and GPU computing

Paul Zimmerman

MPFR author, also the author of Modern Computer Arithmetic (a very very useful book). Also part of the team that factored RSA 240 and 250


Computer Science Books

The Art of Computer Programming

Possibly the best book on computer science ever written, deals primarily with algorithms and their implementations

Modern Computer Arithmetic

A useful book for implementing bignum arithmetic, goes into many, many algorithms and special cases. Basically all you need to write your own MPFR/libbf/GMP library

Advanced Programming in the Unix Environment

Heavily recommended for C programming, teaches the C standard library for UNIX OSes

Math Books

The Elements

Written by Euclid around 300BC, this book is a good introduction to the basics of mathematics starting with the basics of geometry

In my opinion, this should be the first mathematics textbook for schools to use. It’s ridiculous that most schools to teach students geometry without using Euclid’s work.

Prime Numbers and the Riemann Hypothesis

Very useful book, for people of all backgrounds (not just mathematicians) that explains prime numbers, number theory, and the Riemann Hypothesis. Gives multiple formulations, diagrams, and explanations. My favorite book on my favorite problem in all of mathematics (so far)!


On the Number of Primes Less Than a Given Magnitude

Possibly the most influential (and yet still underrated) paper in all of mathematics, I highly recommend this paper. Check out my blog post on the Gamma/Zeta function implementations

Design, Optimization, and Benchmarking of Dense Linear Algebra Algorithms on AMD GPUs

My paper, which discusses my work on porting and performance tuning the MAGMA library

Counterexample To Euler’s Conjecture on Sums of Like Powers

One of my favorite papers, although not particularly explanative. A computer-assisted dis-proof of one of Euler’s conjectures

PolyJIT: Polyhedral Optimization Just in Time

Application of JIT techniques with polyhedral compilation

Diesel: DSL for Linear Algebra and Neural Net Computation on GPUs

Example of a language geared at numerics-heavy compilation (focusing on neural networks)

Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data