Krijthe, Jesse H.
- Detecting hidden confounding in observational data using multiple environments
2022/05/27 by Rickard K. A. Karlsson, Karlsson, Rickard K. A., Jesse H. Krijthe +1 · 2 voices · 3 citations
#stat.ME #cs.LG #stat.ML
- When accurate prediction models yield harmful self-fulfilling prophecies
2023/12/02 by Wouter A. C. van Amsterdam, Nan van Geloven, van Amsterdam, Wouter A. C. +6 · 6 citations
Computer Science · #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Topic Modeling
- The risks of risk assessment: causal blind spots when using prediction models for treatment decisions
2024/02/27 by Nan van Geloven, Ruth H. Keogh, van Geloven, Nan +27 · 1 voice · 2 citations
Mathematics · Computer Science · Economics, Econometrics and Finance · #FOS: Computer and information sciences #Methodology (stat.ME)
- The Peaking Phenomenon in Semi-supervised Learning
2016/10/17 by Jesse H. Krijthe, Krijthe, Jesse H., Marco Loog +1 · 1 citation
Computer Science · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Neural Networks and Applications
- RSSL: Semi-supervised Learning in R
2016/12/23 by Krijthe, Jesse H. · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Robust integration of external control data in randomized trials
2024/06/25 by Karlsson, Rickard, Wang, Guanbo, De Bartolomeis, Piersilvio +2 · 3 citations
#FOS: Computer and information sciences #Methodology (stat.ME)
- Falsification of Unconfoundedness by Testing Independence of Causal Mechanisms
2025/02/10 by Rickard K. A. Karlsson, Jesse H. Krijthe, Karlsson, Rickard K. A. +1 · 1 voice · 1 citation
Computer Science · #Software Engineering Research #Statistical and Computational Modeling #cs.LG #stat.ME #stat.ML