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

News 

Research data management and related topics: know-how for your research project

This series of workshops organised by the ETH Library and Scientific IT Services at ETH Zurich introduces you to varied aspects of research data management. Read more

Coffee Lectures – the new events programme is available now

Time is precious. This is why we host the Coffee Lectures event. Within the 15-​minute timeframe, you receive the information on relevant tools and topics that you need for your academic work. Read more

New open access publishing opportunities from 2023 onwards 

New open access agreements with the American Chemical Society (ACS), Canadian Science Publishing (CSP), Microbiology Society, Springer Nature, Oxford University Press (OUP) and Portland Press. Read more

Recently Added 

  1. SUM Reaction Data: The Chemoton 2.0 Data Set 

    Grimmel, Stephanie A.; Unsleber, Jan Patrick; Reiher, Markus (2022)
    This repository contains the data underlying the results presented in Unsleber, J. P.; Grimmel, S. A.; Reiher, M. <strong>2022</strong>, <em>arXiv:2202.13011 [physics.chem-ph]</em>.
    Dataset
  2. Leisure and Play 

    Fischer-Tiné, Harald (2023)
    A Cultural History of Youth ~ The Cultural History of Youth in the Age of Empire
    Book Chapter
  3. Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning 

    Chen, Le; Ao, Yunke; Tschopp, Florian; et al. (2021)
    Proceedings of Machine Learning Research ~ Proceedings of the 2020 Conference on Robot Learning
    Visual-inertial systems rely on precise calibrations of both camera intrinsics and inter-sensor extrinsics, which typically require manually performing complex motions in front of a calibration target. In this work we present a novel approach to obtain favorable trajectories for visual-inertial system calibration, using model-based deep reinforcement learning. Our key contribution is to model the calibration process as a Markov decision ...
    Conference Paper
  4. Modular Mapping and Learning for Robotics 

    Cramariuc, Andrei (2023)
    The ability to precisely localize a robot within the environment is a core capability for mobile robotics. Knowing a robot’s precise pose permits various tasks, such as navigation in an environment, interaction between multiple agents, or mobile manipulation of an object. Various applications such as, for example, autonomous driving, delivery robots, \ac{ar}, mobile manipulation, and robot inspection greatly benefit from an accurate and ...
    Doctoral Thesis
  5. Identifying key stages of radiation fog evolution using water vapor isotopes 

    Li, Yafei; Eugster, Werner; Riedl, Andreas; et al. (2023)
    Agricultural and Forest Meteorology
    Fog is tied to surface energy and water budgets. However, our knowledge about the processes leading to fog evolution is still fragmentary, and their adequate representation in numerical-weather-prediction and climate models remains challenging. Water vapor isotopes are widely used to investigate Earth's water cycle dynamics and can provide process-based insights into fog evolution. Although isotopes of water vapor and droplets during ...
    Journal Article

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