2 citations · 3 across the 9 of their papers we have counts for
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stat.ML2020★ 1 cited
DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and Regularization
Yaniv Shulman
Modern neural network architectures typically have many millions of parameters and can be pruned significantly without substantial loss in effectiveness which demonstrates they are…
stat.ML2019★ 2 cited
Unsupervised Contextual Anomaly Detection using Joint Deep Variational Generative Models
Yaniv Shulman
A method for unsupervised contextual anomaly detection is proposed using a cross-linked pair of Variational Auto-Encoders for assigning a normality score to an observation. The met…