136 citations · 177 across the 5 of their papers we have counts for
5 papers
Bayesian Benefit-Risk Assessment with Dependent Outcomes via Latent Factor Models
Konstantinos Vamvourellis, Konstantinos Kalogeropoulos, Lawrence Phillips
Approving and assessing new drugs is complex because multiple criteria must be considered simultaneously. A common approach is benefit-risk analysis, often conducted within a Bayes…
Intrinsic uncertainties and where to find them
Francesco Farina, Lawrence Phillips, Nicola J Richmond
We introduce a framework for uncertainty estimation that both describes and extends many existing methods. We consider typical hyperparameters involved in classical training as ran…
Few-Shot Learning with Metric-Agnostic Conditional Embeddings
Nathan Hilliard, Lawrence Phillips, Scott Howland +3
Learning high quality class representations from few examples is a key problem in metric-learning approaches to few-shot learning. To accomplish this, we introduce a novel architec…
Using Social Media to Predict the Future: A Systematic Literature Review
Lawrence Phillips, Chase Dowling, Kyle Shaffer +2
Social media (SM) data provides a vast record of humanity's everyday thoughts, feelings, and actions at a resolution previously unimaginable. Because user behavior on SM is a refle…
Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks
Lawrence Phillips, Nathan Hodas
Increasingly, cognitive scientists have demonstrated interest in applying tools from deep learning. One use for deep learning is in language acquisition where it is useful to know…