11.1k citations · 16.3k across the 88 of their papers we have counts for
6 papers · 1 filter
A Lightweight Neural Model for Biomedical Entity Linking
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
Biomedical entity linking aims to map biomedical mentions, such as diseases and drugs, to standard entities in a given knowledge base. The specific challenge in this context is tha…
Causal inference methods for combining randomized trials and observational studies: a review
Bénédicte Colnet, Imke Mayer, Guanhua Chen +6
With increasing data availability, causal effects can be evaluated across different data sets, both randomized controlled trials (RCTs) and observational studies. RCTs isolate the…
NeuMiss networks: differentiable programming for supervised learning with missing values
Marine Le Morvan, Julie Josse, Thomas Moreau +2
The presence of missing values makes supervised learning much more challenging. Indeed, previous work has shown that even when the response is a linear function of the complete dat…
Fine-grain atlases of functional modes for fMRI analysis
Kamalaker Dadi, Gaël Varoquaux, Antonia Machlouzarides-Shalit +4
Population imaging markedly increased the size of functional-imaging datasets, shedding new light on the neural basis of inter-individual differences. Analyzing these large data en…
NeuroQuery: comprehensive meta-analysis of human brain mapping
Jérôme Dockès, Russell Poldrack, Romain Primet +5
Reaching a global view of brain organization requires assembling evidence on widely different mental processes and mechanisms. The variety of human neuroscience concepts and termin…
Linear predictor on linearly-generated data with missing values: non consistency and solutions
Marine Le Morvan, Nicolas Prost, Julie Josse +2
We consider building predictors when the data have missing values. We study the seemingly-simple case where the target to predict is a linear function of the fully-observed data an…