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Explores the challenges and benefits of scaling language models, emphasizing the importance of scaling laws in estimating optimal model and dataset sizes.
Explores the Red bus/Blue bus paradox, nested logit models, and multivariate extreme value models in transportation.
Provides an overview of Finite Element families, including solid and shell elements, with specific examples like linear hexahedron finite elements.
Covers percolation theory, absorbed polymers, giant molecules, phase transition, scaling assumptions, and universal behavior in percolation models.
Covers the Random Field Ising Model, discussing the concept of disorder and the process of finding the ground state.
Explores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.
