7 citations · 9 across the 3 of their papers we have counts for
3 papers
Contextual Unsupervised Outlier Detection in Sequences
Mohamed A. Zahran, Leonardo Teixeira, Vinayak Rao +1
This work proposes an unsupervised learning framework for trajectory (sequence) outlier detection that combines ranking tests with user sequence models. The overall framework ident…
Deep Lifetime Clustering
S Chandra Mouli, Leonardo Teixeira, Jennifer Neville +1
The goal of lifetime clustering is to develop an inductive model that maps subjects into clusters according to their underlying (unobserved) lifetime distribution. We introduce…
Are Graph Neural Networks Miscalibrated?
Leonardo Teixeira, Brian Jalaian, Bruno Ribeiro
Graph Neural Networks (GNNs) have proven to be successful in many classification tasks, outperforming previous state-of-the-art methods in terms of accuracy. However, accuracy alon…