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Category
Flow matching learns a time-dependent vector field v_t(x, c) whose ODE transports simple noise to complex data, enabling fast, deterministic sampling.
Diffusion models learn to reverse a simple noising process by estimating the score (the gradient of the log density) of data at different noise levels.