One-step Generation in the Post Diffusion Era
A review of one-step generative modeling beyond diffusion-time iteration, covering Consistency Models, CTM, MeanFlow, DMD, and the 2026 Drifting Models framework.
Path Signature: Useful Feature for Timeseries
Study note on path signature in the literature of rough path theory. This post introduces the definition, algebraic structure, and probabilistic interpretation of signatures, bridging rough path theory and modern machine learning, based primarily on *A Primer on the Signature Method in Machine Learning*.
Beyond Defaults: Is Noise Conditioning Necessary for Diffusion Models?
A review of recent research that challenges the necessity of noise level conditioning in generative models, exploring alternative approaches to denoising and flow matching.
PinT algorithms for Diffusion Models
A review of researches that accelerate diffusion models in wall clock time by parallelization.
Test-time scaling in Diffusion Models
A review of researches that explore test-time scaling for diffusion models.