2 citations · 3 across the 2 of their papers we have counts for
3 papers
Neural Networks for Learning Counterfactual G-Invariances from Single Environments
S Chandra Mouli, Bruno Ribeiro
Despite -- or maybe because of -- their astonishing capacity to fit data, neural networks are believed to have difficulties extrapolating beyond training data distribution. This wo…
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…
Typed Linear Algebra for Efficient Analytical Querying
João M. Afonso, Gabriel D. Fernandes, João P. Fernandes +5
This paper uses typed linear algebra (LA) to represent data and perform analytical querying in a single, unified framework. The typed approach offers strong type checking (as in mo…