Neural Arithmetic Units & Experiences as an Independent ML Researcher with Andreas Madsen

Banner Image: Andreas Madsen - Podcast Interview

Join our list for notifications and early access to events

About this Episode

Today we're joined by Andreas Madsen, an independent researcher based in Denmark whose research focuses on developing interpretable machine learning models. While we caught up with Andreas to discuss his ICLR spotlight paper, "Neural Arithmetic Units," we also spend time exploring his experience as an independent researcher. We discuss the difficulties of working with limited resources, the importance of finding peers to collaborate with, and tempering expectations of getting papers accepted to conferences -- something that might take a few tries to get right. In his paper, Andreas notes that Neural Networks struggle to perform exact arithmetic operations over real numbers, but this can be helped with the addition of two NN components: the Neural Addition Unit (NAU), which can learn exact addition and subtraction; and the Neural Multiplication Unit (NMU) that can multiply subsets of a vector.
Connect with Andreas
Read More

More from TWIML

Leave a Reply

Your email address will not be published. Required fields are marked *