Lower-level publication types

Recent Submissions 

  1. New information, new interests? Impact of an occupation finder on the occupational choices of dual vocational education and training students 

    Oswald-Egg, Maria Esther (2025)
    CES Working Paper Series
    When making career-defining decisions, such as choosing an occupation, individuals should be well-informed. This study investigates the impact of a low-cost personalized information intervention on occupational choices in dual vocational education and training (VET) in Switzerland. Using data from an online platform for dual VET positions and a regression discontinuity design (RDD), I analyze how the introduction of an occupation finder ...
    Working Paper
  2. Mapping out the Space of Human Feedback for Reinforcement Learning: A Conceptual Framework 

    Metz, Yannick; Lindner, David; Baur, Raphaël; et al. (2024)
    arXiv
    Reinforcement Learning from Human feedback (RLHF) has become a powerful tool to fine-tune or train agentic machine learning models. Similar to how humans interact in social contexts, we can use many types of feedback to communicate our preferences, intentions, and knowledge to an RL agent. However, applications of human feedback in RL are often limited in scope and disregard human factors. In this work, we bridge the gap between machine ...
    Working Paper
  3. Decoding morphogen patterning of human neural organoids with a multiplexed single-cell transcriptomic screen 

    Sanchís-Calleja, Fátima; Jain, Akanksha; He, Zhisong; et al. (2024)
    Working Paper
  4. RoCK and ROI: Single-cell transcriptomics with multiplexed enrichment of selected transcripts and region-specific sequencing 

    Moro, Giulia; Mallona, Izaskun; Maillard, Joël; et al. (2024)
    Working Paper
  5. Sampling-Based Model Predictive Control for Dexterous Manipulation on a Biomimetic Tendon-Driven Hand 

    Hess, Adrian; Kübler, Alexander; Forrai, Benedek; et al. (2024)
    Biomimetic and compliant robotic hands offer the potential for human-like dexterity, but controlling them is challenging due to high dimensionality, complex contact interactions, and uncertainties in state estimation. Sampling-based model predictive control (MPC), using a physics simulator as the dynamics model, is a promising approach for generating contact-rich behavior. However, sampling-based MPC has yet to be evaluated on physical ...
    Working Paper
  6. The Alzheimer’s Aβ peptide forms biomolecular condensates that trigger amyloid aggregation 

    Šneiderienė, Greta; González Díaz, Alicia; Das Adhikari, Sourav; et al. (2024)
    bioRxiv
    The onset and development of Alzheimer’s disease (AD) is linked to the accumulation of pathological aggregates formed from the normally monomeric amyloid-β peptide within the central nervous system. These Aβ aggregates are increasingly successfully targeted with clinical therapies, but the fundamental molecular steps that trigger the initial nucleation event leading to the conversion of monomeric Aβ peptide into pathological aggregates ...
    Working Paper
  7. <i>DemoTape</i>: Computational demultiplexing of targeted single-cell sequencing data 

    Borgsmüller, Nico; Kuipers, Jack; Gawron, Johannes; et al. (2024)
    Working Paper
  8. On $L^\infty$ stability for wave propagation and for linear inverse problems 

    Alaifari, Rima; Alberti, Giovanni S.; Gauksson, Tandri (2024)
    arXiv
    Stability is a key property of both forward models and inverse problems, and depends on the norms considered in the relevant function spaces. For instance, stability estimates for hyperbolic partial differential equations are often based on energy conservation principles, and are therefore expressed in terms of $L^2$ norms. The focus of this paper is on stability with respect to the $L^\infty$ norm, which is more relevant to detect localized ...
    Working Paper
  9. Innovation und Digitalisierung in der Schweizer Privatwirtschaft – Ergebnisse der Innovationserhebung 2023 

    Spescha, Andrin; Tran, Samantha; Wörter, Martin (2025)
    KOF Studies
    Report
  10. SPACE: A Novel Digital Tool for Assessing Hippocampal Structural Integrity in Older Adults 

    Minta, Karolina; Colombo, Giorgio; Tee, Mervin; et al. (2024)
    Research Square
    Hippocampal atrophy is a hallmark of Alzheimer’s disease and is associated with deficits in navigation. We investigated whether a novel digital assessment, the Spatial Performance Assessment for Cognitive Evaluation (SPACE), can predict hippocampal integrity beyond traditional neuropsychological tests in older adults. Forty older male participants underwent structural MRI and completed the spatial and navigation tasks in SPACE along with ...
    Working Paper
  11. Beyond Traditional Assessments of Cognitive Impairment: Exploring the Potential of Spatial Navigation Tasks 

    Colombo, Giorgio; Minta, Karolina; Thrash, Tyler; et al. (2024)
    medRxiv
    INTRODUCTION Alzheimer’s disease affects spatial abilities that are often overlooked in standard cognitive screening tools. We assessed whether the spatial navigation tasks in the Spatial Performance Assessment for Cognitive Evaluation (SPACE) can complement existing tools such as the Montreal Cognitive Assessment (MoCA). METHODS 348 participants aged 21-76 completed the MoCA, SPACE, and sociodemographic- health questionnaires. Regressions ...
    Working Paper
  12. The role of memory and perspective shifts in systematic biases during object location estimation 

    Segen, Vladislava; Colombo, Giorgio; Avraamides, Marios; et al. (2021)
    bioRxiv
    Our previous research highlighted a systematic bias in a spatial memory task, with participants correctly detecting object movements in the same direction as the perspective shift, whilst misjudging the direction of object movements if those were in the opposite direction to the perspective shift. The aim of the current study was to investigate if the introduction of perspective shifts results in systematic biases in object location ...
    Working Paper
  13. The GPU-based High-order adaptive OpticS Testbench 

    Engler, Byron; Kasper, Markus; Leveratto, Serban; et al. (2024)
    arXiv
    The GPU-based High-order adaptive OpticS Testbench (GHOST) at the European Southern Observatory (ESO) is a new 2-stage extreme adaptive optics (XAO) testbench at ESO. The GHOST is designed to investigate and evaluate new control methods (machine learning, predictive control) for XAO which will be required for instruments such as the Planetary Camera and Spectrograph of ESOs Extremely Large Telescope. The first stage corrections are performed ...
    Working Paper
  14. Stress test framework for evaluating the resilience of transport systems 

    Adey, Bryan T.; Nasrazadani, Hossein; Chambers, Katherine; et al. (2024)
    This document outlines a comprehensive framework for conducting stress tests and evaluating the resilience of transportation systems. It is targeted at stakeholders engaged in transportation planning, risk analysis, and decision-making processes. It includes policymakers, transport authorities, engineers, and consultants, providing them with a standardized procedure to conduct stress tests and estimate the resilience of their system using ...
    Report
  15. A bio-inspired hardware implementation of an analog spike-based hippocampus memory model 

    Casanueva-Morato, Daniel; Ayuso-Martinez, Alvaro; Indiveri, Giacomo; et al. (2024)
    TechRxiv
    The need for processing at the edge the increasing amount of data that is being produced by multitudes of sensors has led to the demand for mode power efficient computational systems, by exploring alternative computing paradigms and technologies. Neuromorphic engineering is a promising approach that can address this need by developing electronic systems that faithfully emulate the computational properties of animal brains. In particular, ...
    Working Paper
  16. Modulating State Space Model with SlowFast Framework for Compute-Efficient Ultra Low-Latency Speech Enhancement 

    Cheng, Longbiao; Pandey, Ashutosh; Xu, Buye; et al. (2024)
    arXiv
    Deep learning-based speech enhancement (SE) methods often face significant computational challenges when needing to meet low-latency requirements because of the increased number of frames to be processed. This paper introduces the SlowFast framework which aims to reduce computation costs specifically when low-latency enhancement is needed. The framework consists of a slow branch that analyzes the acoustic environment at a low frame rate, ...
    Working Paper
  17. Online String Attractors 

    Whittington, Philip (2024)
    In today's data-centric world, fast and effective compression of data is paramount. To measure success towards the second goal, Kempa and Prezza [STOC2018] introduce the string attractor, a combinatorial object unifying dictionary-based compression. Given a string $T \in Σ^n$, a string attractor ($k$-attractor) is a set of positions $Γ\subseteq [1,n]$, such that every distinct substring (of length at most $k$) has at least one occurrence ...
    Report

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