111 citations · 425 across the 26 of their papers we have counts for
28 papers
Robust Bayes-Assisted Conformal Prediction
Kianoosh Ashouritaklimi, Stefano Cortinovis, François Caron
Bayes-assisted conformal prediction combines the strengths of Bayesian modelling with exact, distribution-free frequentist coverage guarantees. Although conformal validity is prese…
Asymptotically Log-Optimal Bayes-Assisted Confidence Sequences for Bounded Means
Valentin Kilian, Stefano Cortinovis, François Caron
Confidence sequences based on test martingales provide time-uniform uncertainty quantification for the mean of bounded IID observations without parametric distributional assumption…
Anytime-valid, Bayes-assisted, Prediction-Powered Inference
Valentin Kilian, Stefano Cortinovis, François Caron
Given a large pool of unlabelled data and a smaller amount of labels, prediction-powered inference (PPI) leverages machine learning predictions to increase the statistical efficien…
Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning
Francois Caron, Fadhel Ayed, Paul Jung +3
We consider gradient-based optimisation of wide, shallow neural networks, where the output of each hidden node is scaled by a positive parameter. The scaling parameters are non-ide…
Non-exchangeable feature allocation models with sublinear growth of the feature sizes
Giuseppe Di Benedetto, François Caron, Yee Whye Teh
Feature allocation models are popular models used in different applications such as unsupervised learning or network modeling. In particular, the Indian buffet process is a flexibl…
Sparse Networks with Core-Periphery Structure
Cian Naik, François Caron, Judith Rousseau
We propose a statistical model for graphs with a core-periphery structure. To do this we define a precise notion of what it means for a graph to have this structure, based on the s…