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Found 5 papers, 2 papers with code
Interpretable Anomaly Detection with Mondrian P{ó}lya Forests on Data Streams
Anomaly detection at scale is an extremely challenging problem of great practicality.
Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data
We propose a new probabilistic method for unsupervised recovery of corrupted data.
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients
The evidence lower bound of the marginal log-likelihood of empirical Bayes decomposes as a sum of local KL divergences between the variational posterior and the true posterior on the query set of each task.
Ranked #11 on
Few-Shot Image Classification
on CIFAR-FS 5-way (1-shot)
Transferring Knowledge across Learning Processes
Approaches that transfer information contained only in the final parameters of a source model will therefore struggle.
Bayesian Nonparametric Crowdsourcing
Crowdsourcing has been proven to be an effective and efficient tool to annotate large datasets.
