Jacob V. R. Pretorius
Nature Computational Science · 2020
A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Whom Jacob V. R. Pretorius trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Jacob V. R. Pretorius's perspective
Ordered by how strongly the researchers Jacob V. R. Pretorius trusts endorse each paper. Same corpus, a different order for every researcher.
- Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
- Dynamic Bayesian Network for Aircraft Wing Health Monitoring Digital Twin
- Reengineering Aircraft Structural Life Prediction Using a Digital Twin
- Digital Twin: Values, Challenges and Enablers From a Modeling Perspective (IEEE Access)
- Data-Driven Science and Engineering
- Learning about physical parameters: the importance of model discrepancy
- Dynamic Data Driven Applications Systems: A New Paradigm for Application Simulations and Measurements (International Conference on Conceptual Structures)
- A Bayesian Approach for Learning and Planning in Partially Observable Markov Decision Processes
- Reinforcement Learning: An Introduction
- Regression Shrinkage and Selection via the Lasso
Their papers
- A probabilistic graphical model foundation for enabling predictive digital twins at scale (2020) — 331 citations