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Found 4 papers, 2 papers with code
Mixed Models with Multiple Instance Learning
Predicting patient features from single-cell data can help identify cellular states implicated in health and disease.
BEL: A Bag Embedding Loss for Transformer enhances Multiple Instance Whole Slide Image Classification
Recent MIL approaches produce highly informative bag level representations by utilizing the transformer architecture's ability to model the dependencies between instances.
Probabilistic Neural Architecture Search
We showcase the advantages of our approach in applications to CIFAR-10 and ImageNet, where our approach outperforms methods with double its computational cost and matches the performance of methods with costs that are three orders of magnitude larger.
Gaussian Process Prior Variational Autoencoders
In this work, we introduce a new model, the Gaussian Process (GP) Prior Variational Autoencoder (GPPVAE), to specifically address this issue.
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