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Masha Naslidnyk
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Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference
A Bharti, M Naslidnyk, O Key, S Kaski, FX Briol
arXiv preprint arxiv:2301.11674, 2023
62023
Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets
E Balkir, M Naslidnyk, D Palfrey, A Mittal
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
62019
Comparing Scale Parameter Estimators for Gaussian Process Regression: Cross Validation and Maximum Likelihood
M Naslidnyk, M Kanagawa, T Karvonen, M Mahsereci
arXiv preprint arXiv:2307.07466, 2023
22023
Invariant Priors for Bayesian Quadrature
M Naslidnyk, J Gonzalez, M Mahsereci
NeurIPS 2021 Workshop. Your Model Is Wrong: Robustness and Misspecification …, 2021
22021
Improving knowledge graph embeddings with inferred entity types
E Balkır, M Naslidnyk, D Palfrey, A Mittal
Proceedings of the 32nd Annual Conference on Neural Information Processing …, 2018
22018
Improved knowledge graph embeddings by using inferred entity types
E Balkir, M Naslidnyk, D Palfrey, A Mittal, S Durrant
2018
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Articles 1–6