From Neurons to Newtons: What the Brain Can Teach Us About Building Physics | Alexei Koulakov

Automated Discovery of Physical Models with Shallow Recurrent Decoders | Nathan Kutz

Quantum Machines Learning Quantum | Gerard Milburn

Towards an AI Co-Scientist: Automatic Governing Law Discovery (Symmetry + Equations) | Jianke Yang

Language Models for Simulating Quantum Many-Body Systems | Juan Felipe Carrasquilla Alvarez

Symbolic Regression, Sparsification, and Kolmogorov-Arnold Networks | Fabian Ruehle

LLM Systems for Literature-Based Scientific Discovery (Scimon, Scideator, CHIMERA) | Tom Hope

Towards a Physics Foundation Model: The General Physics Transformer (GPhyT) | Florian Wiesner

Vignettes from Machine Learning in the Atomistic Sciences: Bespoke and General | Tess Schmidt

AI in Astrophysics: Domain Shift, Model Robustness & Uncertainty | Aleksandra Ciprijanovic

Accelerating Discovery in Collider Physics with Foundation Models | Vinicius Mikuni