Pandaemonium Architecture 6.0

In this course

Jeff Donahue is a machine learning researcher at DeepMind known for work on generative adversarial networks and their scaling to high-fidelity image synthesis. He co-authored foundational papers on GANs that the course readings draw upon to ground discussions of how neural networks learn to generate convincing visual content—a key technical concern when examining AI's capacity to produce and manipulate imagery in society. His work appears in the readings as part of the lineage establishing how modern generative models function, providing the technical scaffolding for critical analysis of synthetic media's cultural implications.

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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