9 citations · 9 across the 3 of their papers we have counts for
3 papers
Towards Worst-Case Guarantees with Scale-Aware Interpretability
Lauren Greenspan, David Berman, Aryeh Brill +9
Neural networks organize information according to the hierarchical, multi-scale structure of natural data. Methods to interpret model internals should be similarly scale-aware, exp…
Exploring the Energy Landscape of RBMs: Reciprocal Space Insights into Bosons, Hierarchical Learning and Symmetry Breaking
J. Quetzalcóatl Toledo-Marin, Anindita Maiti, Geoffrey C. Fox +1
Deep generative models have become ubiquitous due to their ability to learn and sample from complex distributions. Despite the proliferation of various frameworks, the relationship…
Asymptotic theory of in-context learning by linear attention
Yue M. Lu, Mary I. Letey, Jacob A. Zavatone-Veth +2
Transformers have a remarkable ability to learn and execute tasks based on examples provided within the input itself, without explicit prior training. It has been argued that this…