Scalable Computation of Prediction Intervals for Neural Networks via Matrix Sketching. - Alexander Fishkov; Maxim Panov (AIST, 2021)

Nonparametric Uncertainty Quantification for Single Deterministic Neural Network. - Nikita Kotelevskii; Aleksandr Artemenkov; Kirill Fedyanin; Fedor Noskov; Alexander Fishkov; Artem Shelmanov; Artem Vazhentsev; Aleksandr Petiushko; Maxim Panov (NeurIPS, 2022)

NUQ: Nonparametric Uncertainty Quantification for Deterministic Neural Networks. - Nikita Kotelevskii; Aleksandr Artemenkov; Kirill Fedyanin; Fedor Noskov; Alexander Fishkov; Aleksandr Petiushko; Maxim Panov (CoRR, 2022)

Selective Nonparametric Regression via Testing. - Fedor Noskov; Alexander Fishkov; Maxim Panov (ACML, 2023)

Efficient Conformal Prediction under Data Heterogeneity. - Vincent Plassier; Nikita Kotelevskii; Aleksandr Rubashevskii; Fedor Noskov; Maksim Velikanov; Alexander Fishkov; Samuel Horváth; Martin Takác 001; Eric Moulines; Maxim Panov (AISTATS, 2024)

Conditionally valid Probabilistic Conformal Prediction. - Vincent Plassier; Alexander Fishkov; Maxim Panov; Eric Moulines (CoRR, 2024)

Probabilistic Conformal Prediction with Approximate Conditional Validity. - Vincent Plassier; Alexander Fishkov; Mohsen Guizani; Maxim Panov; Eric Moulines (ICLR, 2025)

Rectifying Conformity Scores for Better Conditional Coverage. - Vincent Plassier; Alexander Fishkov; Victor Dheur; Mohsen Guizani; Souhaib Ben Taieb; Maxim Panov; Eric Moulines (CoRR, 2025)