6 citations · 7 across the 2 of their papers we have counts for
3 papers
Dropout as a Structured Shrinkage Prior
Eric Nalisnick, José Miguel Hernández-Lobato, Padhraic Smyth
Dropout regularization of deep neural networks has been a mysterious yet effective tool to prevent overfitting. Explanations for its success range from the prevention of "co-adapte…
Mondrian Processes for Flow Cytometry Analysis
Disi Ji, Eric Nalisnick, Padhraic Smyth
Analysis of flow cytometry data is an essential tool for clinical diagnosis of hematological and immunological conditions. Current clinical workflows rely on a manual process calle…
A Scale Mixture Perspective of Multiplicative Noise in Neural Networks
Eric Nalisnick, Anima Anandkumar, Padhraic Smyth
Corrupting the input and hidden layers of deep neural networks (DNNs) with multiplicative noise, often drawn from the Bernoulli distribution (or 'dropout'), provides regularization…