activity
20202024
most citedBayesian Active Learning with Fully Bayesian Gaussian Processes

10 citations · 17 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2024★ 1 cited

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…

cs.LG2023

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…

cs.LG2023

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…

cs.LG2023★ 1 cited

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…

stat.AP2022★ 2 cited

Determining Causality in Travel Mode Choice

Rishabh Singh Chauhan, Christoffer Riis, Shishir Adhikari +4

This article presents one of the pioneering studies on causal modeling in travel mode choice decision-making using causal discovery algorithms. These models are a major advancement…

cs.LG2022★ 10 cited

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…

cs.CV2020★ 3 cited

On the Limits to Multi-Modal Popularity Prediction on Instagram -- A New Robust, Efficient and Explainable Baseline

Christoffer Riis, Damian Konrad Kowalczyk, Lars Kai Hansen

Our global population contributes visual content on platforms like Instagram, attempting to express themselves and engage their audiences, at an unprecedented and increasing rate.…