1 citations · 1 across the 7 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2023
A Quantitative Approach to Predicting Representational Learning and Performance in Neural Networks
Ryan Pyle, Sebastian Musslick, Jonathan D. Cohen +1
A key property of neural networks (both biological and artificial) is how they learn to represent and manipulate input information in order to solve a task. Different types of repr…
cs.LG2023
Beyond Transformers for Function Learning
Simon Segert, Jonathan Cohen
The ability to learn and predict simple functions is a key aspect of human intelligence. Recent works have started to explore this ability using transformer architectures, however…