jwuphysics

Deep neural networks can be thought of as compositions of many simple transformations, each represented by a layer with trainable parameters.

AI is here, and its impacts on education cannot be overstated.

With the Euclid and Roman Space Telescope missions ready to image billions of galaxies, we’ll need data-driven methods to find new, rare phenomena that exist outside human-defined taxonomies!

This post discusses how graph neural networks (GNNs) can model the galaxy–halo connection within its large-scale surroundings.

The Eleven Laws of Showrunning by Javier Grillo-Marxuach is full of useful advice for management and operations.

In the book Impro: Improvisation and the Theatre, Keith Johnstone recounts a moment between a teacher and a special needs student.

Many physical phenomena exhibit relational inductive biases and can be represented as mathematical graphs.

If you’re a blogger or researcher sharing your work online, you’ve probably wondered: is social media actually useful for disseminating your writing?

I am a self-confessed productivity junkie.

Here’s a casual introduction to foundation models and how they might impact astronomy research in the coming years.