1 citations · 2 across the 5 of their papers we have counts for
6 papers
Multivariate Latent Recalibration for Conditional Normalizing Flows
Victor Dheur, Souhaib Ben Taieb
Reliably characterizing the full conditional distribution of a multivariate response variable given a set of covariates is crucial for trustworthy decision-making. However, misspec…
A Unified Comparative Study with Generalized Conformity Scores for Multi-Output Conformal Regression
Victor Dheur, Matteo Fontana, Yorick Estievenart +2
Conformal prediction provides a powerful framework for constructing distribution-free prediction regions with finite-sample coverage guarantees. While extensively studied in univar…
Rectifying Conformity Scores for Better Conditional Coverage
Vincent Plassier, Alexander Fishkov, Victor Dheur +4
We present a new method for generating confidence sets within the split conformal prediction framework. Our method performs a trainable transformation of any given conformity score…
Probabilistic Calibration by Design for Neural Network Regression
Victor Dheur, Souhaib Ben Taieb
Generating calibrated and sharp neural network predictive distributions for regression problems is essential for optimal decision-making in many real-world applications. To address…
Distribution-Free Conformal Joint Prediction Regions for Neural Marked Temporal Point Processes
Victor Dheur, Tanguy Bosser, Rafael Izbicki +1
Sequences of labeled events observed at irregular intervals in continuous time are ubiquitous across various fields. Temporal Point Processes (TPPs) provide a mathematical framewor…
A Large-Scale Study of Probabilistic Calibration in Neural Network Regression
Victor Dheur, Souhaib Ben Taieb
Accurate probabilistic predictions are essential for optimal decision making. While neural network miscalibration has been studied primarily in classification, we investigate this…