5 papers
Deep neural networks as lattice gauge theories
Ro Jefferson, Shradha Ramakrishnan
We modify the NN/QFT duality [1] to incorporate the layerwise permutation symmetry of the network, resulting in a -dimensional lattice gauge theory, in which each layer…
Predictive Coding Networks and Inference Learning: Tutorial and Survey
Björn van Zwol, Ro Jefferson, Egon L. van den Broek
Recent years have witnessed a growing call for renewed emphasis on neuroscience-inspired approaches in artificial intelligence research, under the banner of NeuroAI. A prime exampl…
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…
Algebraic perturbation theory: traversable wormholes and generalized entropy beyond subleading order
Shadi Ali Ahmad, Ro Jefferson
The crossed product has recently emerged as an important ingredient in describing algebras of observables for quantum field theory and gravity. We combine this with perturbation th…
Wilsonian Renormalization of Neural Network Gaussian Processes
Jessica N. Howard, Ro Jefferson, Anindita Maiti +1
Separating relevant and irrelevant information is key to any modeling process or scientific inquiry. Theoretical physics offers a powerful tool for achieving this in the form of th…