10 citations · 17 across the 7 of their papers we have counts for
5 papers · 1 filter
Bayesian Active Learning for Censored Regression
Frederik Boe Hüttel, Christoffer Riis, Filipe Rodrigues +1
Bayesian active learning is based on information theoretical approaches that focus on maximising the information that new observations provide to the model parameters. This is comm…
Applied metamodelling for ATM performance simulations
Christoffer Riis, Francisco N. Antunes, Tatjana Bolić +4
The use of Air traffic management (ATM) simulators for planing and operations can be challenging due to their modelling complexity. This paper presents XALM (eXplainable Active Lea…
Learning and Generalizing Polynomials in Simulation Metamodeling
Jesper Hauch, Christoffer Riis, Francisco C. Pereira
The ability to learn polynomials and generalize out-of-distribution is essential for simulation metamodels in many disciplines of engineering, where the time step updates are descr…
NOSTROMO: Lessons learned, conclusions and way forward
Mayte Cano, Andrés Perillo, Juan Antonio López +15
This White Paper sets out to explain the value that metamodelling can bring to air traffic management (ATM) research. It will define metamodelling and explore what it can, and cann…
Bayesian Active Learning with Fully Bayesian Gaussian Processes
Christoffer Riis, Francisco Antunes, Frederik Boe Hüttel +2
The bias-variance trade-off is a well-known problem in machine learning that only gets more pronounced the less available data there is. In active learning, where labeled data is s…