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Found 3 papers, 2 papers with code
Protein Discovery with Discrete Walk-Jump Sampling
We resolve difficulties in training and sampling from a discrete generative model by learning a smoothed energy function, sampling from the smoothed data manifold with Langevin Markov chain Monte Carlo (MCMC), and projecting back to the true data manifold with one-step denoising.
Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation
Detection of Out-of-Distribution (OOD) samples in real time is a crucial safety check for deployment of machine learning models in the medical field.
Deep Denerative Models for Drug Design and Response
Designing new chemical compounds with desired pharmaceutical properties is a challenging task and takes years of development and testing.
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