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📚TheoryIntermediate

Flow Matching

Flow matching learns a time-dependent vector field v_t(x, c) whose ODE transports simple noise to complex data, enabling fast, deterministic sampling.

#flow matching#conditional flow matching#rectified flow+11
📚TheoryAdvanced

Diffusion Models (Score-Based)

Score-based diffusion models corrupt data by gradually adding Gaussian noise and then learn to reverse this process by estimating the score, the gradient of the log-density.

#diffusion models
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#probability flow ode
#score-based modeling
#ddpm
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📚TheoryAdvanced

Diffusion Models Theory

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.

#diffusion models#ddpm#score matching+12