5 papers
Symbolic Learning of Topological Bands in Photonic Crystals
Ali Ghorashi, Sachin Vaidya, Ziming Liu +4
Topological photonic crystals (PhCs) that support disorder-resistant modes, protected degeneracies, and robust transport have recently been explored for applications in waveguiding…
Harmonic Loss Trains Interpretable AI Models
David D. Baek, Ziming Liu, Riya Tyagi +1
In this paper, we introduce harmonic loss as an alternative supervisory signal for training neural networks and large language models (LLMs). Harmonic loss differs from standard cr…
Second Order Ensemble Langevin Method for Sampling and Inverse Problems
Ziming Liu, Andrew M. Stuart, Yixuan Wang
We propose a sampling method based on an ensemble approximation of second order Langevin dynamics. The log target density is appended with a quadratic term in an auxiliary momentum…
Do Two AI Scientists Agree?
Xinghong Fu, Ziming Liu, Max Tegmark
When two AI models are trained on the same scientific task, do they learn the same theory or two different theories? Throughout history of science, we have witnessed the rise and f…
GenEFT: Understanding Statics and Dynamics of Model Generalization via Effective Theory
David D. Baek, Ziming Liu, Max Tegmark
We present GenEFT: an effective theory framework for shedding light on the statics and dynamics of neural network generalization, and illustrate it with graph learning examples. We…