Improving cross-validation based classifier selection using meta-learning. - Jesse H. Krijthe; Tin Kam Ho; Marco Loog (ICPR, 2012)

Implicitly Constrained Semi-supervised Linear Discriminant Analysis. - Jesse H. Krijthe; Marco Loog (ICPR, 2014)

Implicitly Constrained Semi-supervised Least Squares Classification. - Jesse H. Krijthe; Marco Loog (IDA, 2015)

On Measuring and Quantifying Performance: error rates, surrogate Loss, and an Example in Semi-Supervised Learning. - Marco Loog; Jesse H. Krijthe; Are Charles Jensen (Handbook of Pattern Recognition and Computer Vision, 2016)

RSSL: Semi-supervised Learning in R. - Jesse H. Krijthe (RRPR@ICPR, 2016)

Reproducible Pattern Recognition Research: The Case of Optimistic SSL. - Jesse H. Krijthe; Marco Loog (RRPR@ICPR, 2016)

Optimistic semi-supervised least squares classification. - Jesse H. Krijthe; Marco Loog (ICPR, 2016)

The Peaking Phenomenon in Semi-supervised Learning. - Jesse H. Krijthe; Marco Loog (S+SSPR, 2016)

The Pessimistic Limits of Margin-based Losses in Semi-supervised Learning. - Jesse H. Krijthe; Marco Loog (CoRR, 2016)

Feature-Level Domain Adaptation. - Wouter M. Kouw; Laurens J. P. van der Maaten; Jesse H. Krijthe; Marco Loog (J. Mach. Learn. Res., 2016)

On Measuring and Quantifying Performance: Error Rates, Surrogate Loss, and an Example in SSL. - Marco Loog; Jesse H. Krijthe; Are Charles Jensen (CoRR, 2017)

Nuclear Discrepancy for Active Learning. - Tom J. Viering; Jesse H. Krijthe; Marco Loog (CoRR, 2017)

Projected estimators for robust semi-supervised classification. - Jesse H. Krijthe; Marco Loog (Mach. Learn., 2017)

Robust semi-supervised least squares classification by implicit constraints. - Jesse H. Krijthe; Marco Loog (Pattern Recognit., 2017)

The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning. - Jesse H. Krijthe; Marco Loog (NeurIPS, 2018)

Robust Importance-Weighted Cross-Validation Under Sample Selection Bias. - Wouter M. Kouw; Jesse H. Krijthe; Marco Loog (MLSP, 2019)

Nuclear discrepancy for single-shot batch active learning. - Tom J. Viering; Jesse H. Krijthe; Marco Loog (Mach. Learn., 2019)

A Brief Prehistory of Double Descent. - Marco Loog; Tom J. Viering; Alexander Mey; Jesse H. Krijthe; David M. J. Tax (CoRR, 2020)

ReproducedPapers.org: Openly Teaching and Structuring Machine Learning Reproducibility. - Burak Yildiz; Hayley Hung; Jesse H. Krijthe; Cynthia C. S. Liem; Marco Loog; Gosia Migut; Frans A. Oliehoek; Annibale Panichella; Przemyslaw Pawelczak; Stjepan Picek; Mathijs de Weerdt; Jan van Gemert (RRPR, 2021)

Explaining Two Strange Learning Curves. - Zhiyi Chen; Marco Loog; Jesse H. Krijthe (BNAIC/BENELEARN, 2022)

Combining observational datasets from multiple environments to detect hidden confounding. - Rickard K. A. Karlsson; Jesse H. Krijthe (CoRR, 2022)

Detecting hidden confounding in observational data using multiple environments. - Rickard Karlsson; Jesse H. Krijthe (NeurIPS, 2023)

Also for k-means: more data does not imply better performance. - Marco Loog; Jesse H. Krijthe; Manuele Bicego (Mach. Learn., 2023)

Causal inference using observational intensive care unit data: a scoping review and recommendations for future practice. - J. M. Smit; Jesse H. Krijthe; W. M. R. Kant; J. A. Labrecque; M. Komorowski; D. A. M. P. J. Gommers; Jasper van Bommel; Marcel J. T. Reinders; Michel E. van Genderen (npj Digit. Medicine, 2023)

Counterintuitive Behavior of Clustering Quality: Findings for K-Means on Synthetic and Real Data. - Marco Loog; Jesse H. Krijthe; Manuele Bicego (IDA, 2025)

Are Interactive Visualizations in Machine Learning Education Helping Students? - Ilinca Rentea; Gosia Migut; Jesse H. Krijthe (ITiCSE (1), 2025)

When accurate prediction models yield harmful self-fulfilling prophecies. - Wouter A. C. van Amsterdam; Nan van Geloven; Jesse H. Krijthe; Rajesh Ranganath; Giovanni Cinà (Patterns, 2025)

Falsification of Unconfoundedness by Testing Independence of Causal Mechanisms. - Rickard K. A. Karlsson; Jesse H. Krijthe (CoRR, 2025)

Qini curve estimation under clustered network interference. - Rickard K. A. Karlsson; Bram van den Akker; Felipe Moraes; Hugo Manuel Proença; Jesse H. Krijthe (CoRR, 2025)

Robust estimation of heterogeneous treatment effects in randomized trials leveraging external data. - Rickard Karlsson; Piersilvio De Bartolomeis; Issa J. Dahabreh; Jesse H. Krijthe (CoRR, 2025)