Generative Adversarial Networks (GANs) are a class of deep learning models that learn to produce new (or pseudo-real) data. Their advent in 2014 and refinement thereafter have led to them dominating ...

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This course provides a comprehensive introduction to diffusion models and flow models for generative AI, covering both theoretical foundations and methodological advancements. The course is divided ...

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Diffusion models gradually refine and produce a requested output, sometimes starting from random noise—values generated by the model itself—and sometimes working from user-provided data. Think of ...

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“Macro placement is a vital step in digital circuit design that defines the physical location of large collections of components, known as macros, on a 2-dimensional chip. The physical layout obtained ...