Research Line Resilience (part of LIRS program)

Fingerprint Dive into the research topics where Research Line Resilience (part of LIRS program) is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.

education Social Sciences

employability Social Sciences

learning Earth & Environmental Sciences

resources Social Sciences

expert Social Sciences

higher education Earth & Environmental Sciences

poster Social Sciences

modeling Earth & Environmental Sciences

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Profiles

Robert Jan R.J. Blomme

Department Organisation - Full Professor
Research Line Innovation (part of LIRS program) - Researcher
Research Line Learning (part of LIRS program) - Researcher
Research Line Resilience (part of LIRS program) - Researcher

Person

Stefano Bromuri

Department Information Science and Business Processes - Associate professor
Research Line Resilience (part of LIRS program) - Researcher

Person: Academic

Co-Adapt: Co-Adapt: Climate Adaptation Through Co-creation

Lansu, A., Bogatinoska, B., Floor, J., Dekker, S. & van Wijnen, J.

1/02/19 → 30/09/22

Project: Research

Research Output 2014 2019

5th generation district heating and cooling systems as a solution for renewable urban thermal energy supply

Boesten, S., Ivens, W., Dekker, S. C. & Eijdems, H., 20 Sep 2019, In : Advances in Geosciences. 49, p. 129-136

Research output: Contribution to journal › Article › Academic › peer-review

Open Access

cooling systems

thermal energy

cooling

fossil fuels

heating

A comparison between discrete and continuous time Bayesian networks in learning from clinical time series data with irregularity

Liu, M., Stella, F., Hommersom, A., Lucas, P. J. F., Boer, L. & Bischoff, E., Apr 2019, In : Artificial Intelligence in Medicine. 95, p. 104-117 14 p.

Research output: Contribution to journal › Article › Academic › peer-review

A Data-Driven Exploration of Hypotheses on Disease Dynamics

Bueno, M. L. P., Hommersom, A., Lucas, P. J. F. & Janzing, J., 30 May 2019, Artificial Intelligence in Medicine: 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Poznan, Poland, June 26–29, 2019, Proceedings. Riaño, D., Wilk, S. & ten Teije, A. (eds.). Cham: Springer International Publishing AG, p. 170-179 10 p. (Lecture Notes in Computer Science (LNCS), Vol. 11526).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Unsupervised learning

Hidden Markov models