slides

Flow Matching

Introduction to flow matching as a continuous-time generative modeling framework, covering transport, conditional objectives, and training/sampling algorithms.

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Diffusion

Overview of diffusion models from forward noising processes to reverse-time dynamics, score matching, and sampling algorithms.

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Transformer

Primer on transformer origins, architecture, self-attention, scaling behavior, and variants used in modern generative modeling.

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Git

Practical introduction to Git fundamentals, VS Code workflows, and collaborative development with GitHub.

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