Demonstrates that covariance matching procedure improves synthetic data quality for training neural networks better than mean shift or other approaches.
Proposes information-theoretic Lagrangian formulation to balance simplicity and expressiveness in Koopman representation learning for dynamical systems.
einx is universal notation for tensor operations using vectorization, reducing large APIs to small consistent operation sets.
MrRoPE generalizes RoPE-extension via radix system conversion, achieving train-short-test-long with doubled effective context window.