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Found 3 papers, 1 papers with code
Enhancing Image Layout Control with Loss-Guided Diffusion Models
In particular, conditional diffusion models allow one to specify the contents of the desired image using a simple text prompt.
Unsupervised Learning of Rydberg Atom Array Phase Diagram with Siamese Neural Networks
We introduce an unsupervised machine learning method based on Siamese Neural Networks (SNN) to detect phase boundaries.
Extremal learning: extremizing the output of a neural network in regression problems
Finding the extremizing input of an approximated model is formulated as the training of an additional neural network with a loss function that minimizes when the extremizing input is achieved.
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