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Found 6 papers, 1 papers with code
Neural network representation of quantum systems
It has been proposed that random wide neural networks near Gaussian process are quantum field theories around Gaussian fixed points.
Understanding Diffusion Models by Feynman's Path Integral
Score-based diffusion models have proven effective in image generation and have gained widespread usage; however, the underlying factors contributing to the performance disparity between stochastic and deterministic (i. e., the probability flow ODEs) sampling schemes remain unclear.
Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE
Understanding the inner workings of neural networks, including transformers, remains one of the most challenging puzzles in machine learning.
Complete characterization of robust perfect adaptation in biochemical reaction networks
The present results indicate that an RPA property is essentially equivalent to the existence of a "topological invariant", which is an instance of what we call the "Robust Adaptation is Topological"(RAT) principle.
Robust Perfect Adaptation of Reaction Fluxes Ensured by Network Topology
Maintaining stability in an uncertain environment is essential for proper functioning of living systems.
Structural reduction of chemical reaction networks based on topology
A subnetwork can be eliminated systematically to give a reduced system with fewer degrees of freedom.
