Repository for Publications and Research Data

Search ETH Zurich’s Research Collection for scientific publications and research data or submit your own research output. Read more


ORCID author identifiers in the Research Collection

The Open Researcher and Contributor ID (ORCID) enables researchers to be identified clearly and publications attributed correctly to people – which is now possible in ETH Zurich’s Research Collection, too. Read more

National Open Access Conference 2018

swissuniversities invites guests to the National Open Access Conference at the University of Lausanne on Friday, 26 October 2018. Read more

Storing and archiving data safely

Many data storage devices and certain file formats no longer run on your computer after a couple of years. So what is the most effective way to secure data and store it for a long time? ETH Library’s Digital Curation Office to the rescue! Read more

Recently Added 

  1. Late Gothic Constructions in Müstair and Meran 

    Maissen, Manuel; Gantner, Martin; Holzer, Stefan M. (2018)
    Building Knowledge, Constructing Histories, Proceedings of the 6th International Congress on Construction History (6ICCH 2018), July 9-13, 2018, Brussels, Belgium
    Conference Paper
  2. Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care 

    Schwab, Patrick; Keller, Emanuela; Muroi, Carl; et al. (2018)
    Conference Paper
  3. Real-time merging traffic control for throughput maximization at motorway work zones 

    Tympakianaki, Athina; Spiliopoulou, Anastasia D.; Kouvelas, Anastasios; et al. (2012)
    Conference Paper
  4. Congestion control in urban networks via feedback gating 

    Keyvan-Ekbatani, Mehdi; Kouvelas, Anastasios; Papamichail, Ioannis; et al. (2012)
    Conference Paper
  5. A learning technique for deploying self-tuning traffic control systems 

    Kouvelas, Anastasios; Papageorgiou, Markos; Kosmatopoulos, Elias B.; et al. (2011)
    2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)
    Currently, a considerable amount of human effort and time is spent for initialization or calibration of operational traffic control systems. Typically, this optimization (fine-tuning) procedure is conducted manually, via trial-and-error, relying on expertise and human judgment and does not always lead to a desirable outcome. This paper presents a new learning/adaptive algorithm that enables automatic fine-tuning of general traffic control ...
    Conference Paper

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