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Found 4 papers, 0 papers with code
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.
Deconfining Phase Boundary of Rapidly Rotating Hot and Dense Matter and Analysis of Moment of Inertia
We discuss the effect of rapid rotation on the phase diagram of hadronic matter.
High Energy Physics - Phenomenology Nuclear Theory
Extensive Studies of the Neutron Star Equation of State from the Deep Learning Inference with the Observational Data Augmentation
We discuss deep learning inference for the neutron star equation of state (EoS) using the real observational data of the mass and the radius.
Featuring the topology with the unsupervised machine learning
Images of line drawings are generally composed of primitive elements.
