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Found 3 papers, 3 papers with code
Operating critical machine learning models in resource constrained regimes
The resource consumption of deep learning models in terms of amount of training data, compute and energy costs are known to be massive.
Explicit Temporal Embedding in Deep Generative Latent Models for Longitudinal Medical Image Synthesis
This, in contrast to previous methods, allows us to synthesize continuous, smooth, and high-quality longitudinal volumetric data with limited supervision.
Interpreting Latent Spaces of Generative Models for Medical Images using Unsupervised Methods
The results show that unsupervised methods to discover interpretable directions in GANs generalize to VAEs and can be applied to medical images.
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