Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets. - Esma Balkir; Masha Naslidnyk; Dave Palfrey; Arpit Mittal (EMNLP/IJCNLP (1), 2019)

Invariant Priors for Bayesian Quadrature. - Masha Naslidnyk; Javier Gonzalez; Maren Mahsereci (CoRR, 2021)

Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference. - Ayush Bharti; Masha Naslidnyk; Oscar Key; Samuel Kaski; François-Xavier Briol (ICML, 2023)

Conditional Bayesian Quadrature. - Zonghao Chen; Masha Naslidnyk; Arthur Gretton; François-Xavier Briol (UAI, 2024)

Comparing Scale Parameter Estimators for Gaussian Process Interpolation with the Brownian Motion Prior: Leave-One-Out Cross Validation and Maximum Likelihood. - Masha Naslidnyk; Motonobu Kanagawa; Toni Karvonen; Maren Mahsereci (SIAM/ASA J. Uncertain. Quantification, 2025)

Nested Expectations with Kernel Quadrature. - Zonghao Chen; Masha Naslidnyk; François-Xavier Briol (CoRR, 2025)

Kernel Quantile Embeddings and Associated Probability Metrics. - Masha Naslidnyk; Siu Lun Chau; François-Xavier Briol; Krikamol Muandet (CoRR, 2025)