Pandaemonium Architecture 6.0

In this course

Jeff Donahue is a machine learning researcher at DeepMind known for foundational work on generative adversarial networks and image synthesis at scale. He appears as a co-author on the "Large Scale GAN Training for High Fidelity Natural Image Synthesis" paper, which is central to understanding how contemporary AI systems generate photorealistic images—a key technical capability shaping debates about synthetic media and computational aesthetics in the course. His work bridges the gap between theoretical generative models and their practical deployment, making visible how architectural choices in neural networks directly enable or constrain artistic and representational possibilities.

Mentioned in 2 readings

Andrew Brock

et al., LARGE SCALE GAN TRAINING FOR HIGH FIDELITY NATURAL IMAGE SYNTHESIS

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Large Scale GAN Training for High Fidelity Natural Image Synthesis Andrew Brock\† Heriot-Watt University ajb5@hw.ac.uk Jeff Donahue† DeepMind jeffdonahue@google.com Karen Simonyan† DeepMind simonyan@google.com Abstract Despite recent p…

Robin Rombach

et al., High-Resolution Image Synthesis with Latent Diffusion Models

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6. Conclusion We have presented latent diffusion models, a simple and efficient way to significantly improve both the training and sampling efficiency of denoising diffusion models without degrading their quality. Based on this and our cro…

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