Jesse H. Krijthe

Assistant Professor, Delft University of Technology

Joined

July 2019

Names

Jesse H. Krijthe (Preferred)

JH Krijthe

Jesse Krijthe

Emails

****@gmail.com (Confirmed)

****@tudelft.nl (Confirmed)

****@cs.ru.nl (Confirmed)

****@ru.nl (Confirmed)

Personal Links

Career & Education History

Assistant Professor

Delft University of Technology (tudelft.nl)

2020 – Present

Postdoc

Radboud University Nijmegen (ru.nl)

2017 – 2019

PhD student

Leiden University (lumc.nl)

2012 – 2016

MS student

Delft University of Technology (tudelft.nl)

2010 – 2012

Advisors, Relations & Conflicts

Postdoc Advisor

Tom Heskes

2016 – 2019

PhD Advisor

Marco Loog

2010 – 2016

Expertise

causal inference

heterogeneous treatment effects

statistical learning

adaptive data analysis

2017 – Present

semi-supervised learning

meta-learning

2010 – 2018

Publications

A Brief Prehistory of Double Descent
Marco Loog, Tom Julian Viering, Alexander Mey, JH Krijthe, David Tax
- 09 Feb 2023 (modified: 09 Feb 2023)
- OpenReview Archive Direct Upload
- Readers: Everyone
Also for k-means: more data does not imply better performance
Marco Loog, Jesse H. Krijthe, Manuele Bicego
- Published: 01 Jan 2023, Last Modified: 13 Feb 2024
- Mach. Learn. 2023
- Readers: Everyone
Combining observational datasets from multiple environments to detect hidden confounding
Rickard K. A. Karlsson, Jesse H. Krijthe
- Published: 01 Jan 2022, Last Modified: 12 May 2023
- CoRR 2022
- Readers: Everyone
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
- 2021 (modified: 10 Nov 2022)
- RRPR 2021
- Readers: Everyone
A Brief Prehistory of Double Descent
Marco Loog, Tom J. Viering, Alexander Mey, Jesse H. Krijthe, David M. J. Tax
- 2020 (modified: 15 May 2025)
- CoRR 2020
- Readers: Everyone
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
- 2020 (modified: 10 Nov 2022)
- CoRR 2020
- Readers: Everyone
Nuclear discrepancy for single-shot batch active learning
Tom J. Viering, Jesse H. Krijthe, Marco Loog
- 2019 (modified: 15 May 2025)
- Mach. Learn. 2019
- Readers: Everyone
Robust Importance-Weighted Cross-Validation Under Sample Selection Bias
Wouter M. Kouw, Jesse H. Krijthe, Marco Loog
- Published: 01 Jan 2019, Last Modified: 07 Feb 2024
- MLSP 2019
- Readers: Everyone
The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning
Jesse H. Krijthe, Marco Loog
- 2018 (modified: 11 Nov 2022)
- NeurIPS 2018
- Readers: Everyone
Nuclear Discrepancy for Active Learning
Tom J. Viering, Jesse H. Krijthe, Marco Loog
- 2017 (modified: 15 May 2025)
- CoRR 2017
- Readers: Everyone

View all 11 publications