26 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of St.GallenCH12 papers
- ETH ZurichCH3 papers
- KU LeuvenBE2 papers
- OST - Ostschweizer FachhochschuleCH2 papers
- RWTH Aachen UniversityDE2 papers
- Swiss Finance InstituteCH2 papers
- University of OxfordGB2 papers
- Argonne National LaboratoryUS1 paper
- Deutsche BundesbankDE1 paper
- École Polytechnique Fédérale de LausanneCH1 paper
- Federal Department of FinanceCH1 paper
- Frankfurt School of Finance & ManagementDE1 paper
14 papers
Mind the Trust Gap: Identifying (Mis)alignments in Teacher-Student Views Toward Control and Agency in K-12 Classroom AI
Tomohiro Nagashima, Lisa Siegrist, Niklas Scholz +3
As Artificial Intelligence (AI)-based technologies have been integrated into school classrooms where multiple stakeholders (with different roles) interact with each other, it is cr…
Platforms' Research API Data Access: What Users See vs. What Researchers can Retrieve
Luka Bekavac, Simon Mayer
Article 40(12) of the Digital Services Act (DSA) requires Very Large Online Platforms (VLOPs) to provide vetted researchers with access to publicly accessible data. While prior wor…
A Convexity-dependent Two-Phase Training Algorithm for Deep Neural Networks
Tomas Hrycej, Bernhard Bermeitinger, Massimo Pavone +2
The key task of machine learning is to minimize the loss function that measures the model fit to the training data. The numerical methods to do this efficiently depend on the prope…
GeHirNet: A Gender-Aware Hierarchical Model for Voice Pathology Classification
Fan Wu, Kaicheng Zhao, Elgar Fleisch +1
AI-based voice analysis shows promise for disease diagnostics, but existing classifiers often fail to accurately identify specific pathologies because of gender-related acoustic va…
Diffusion-Scheduled Denoising Autoencoders for Anomaly Detection in Tabular Data
Timur Sattarov, Marco Schreyer, Damian Borth
Anomaly detection in tabular data remains challenging due to complex feature interactions and the scarcity of anomalous examples. Denoising autoencoders rely on fixed-magnitude noi…
A Domain-specific Language and Architecture for Detecting Process Activities from Sensor Streams in IoT
Ronny Seiger, Daniel Locher, Marco Kaufmann +1
Modern Internet of Things (IoT) systems are equipped with a large quantity of sensors providing real-time data about the current operations of their components, which is crucial fo…
Reviewriter: AI-Generated Instructions For Peer Review Writing
Xiaotian Su, Thiemo Wambsganss, Roman Rietsche +2
Large Language Models (LLMs) offer novel opportunities for educational applications that have the potential to transform traditional learning for students. Despite AI-enhanced appl…
Digital Twins of Business Processes: A Research Manifesto
Fabrizio Fornari, Ivan Compagnucci, Massimo Callisto De Donato +20
Modern organizations necessitate continuous business processes improvement to maintain efficiency, adaptability, and competitiveness. In the last few years, the Internet of Things,…
Continual Learning in the Presence of Repetition
Hamed Hemati, Lorenzo Pellegrini, Xiaotian Duan +11
Continual learning (CL) provides a framework for training models in ever-evolving environments. Although re-occurrence of previously seen objects or tasks is common in real-world p…
From droop to optimality: The potential of volt/var control for power distribution grid enhancement
Jonas G. Matt, Lukas Ortmann, Saverio Bolognani +1
When high amounts of active power are injected into power distribution grids, the overall power flow is limited because voltages reach their upper acceptable limits. Volt/var contr…
Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models
Timo Dimitriadis, Roxana Halbleib, Jeannine Polivka +3
This paper analyzes the benefits of sampling intraday returns in intrinsic time for the realized variance (RV) estimator. We theoretically show in finite samples that depending on…
Fake News in Social Networks
Christoph Aymanns, Jakob Foerster, Co-Pierre Georg +1
We propose multi-agent reinforcement learning as a new method for modeling fake news in social networks. This method allows us to model human behavior in social networks both in un…
Naive Diversification Preferences and their Representation
Enrico G. De Giorgi, Ola Mahmoud
A widely applied diversification paradigm is the naive diversification choice heuristic. It stipulates that an economic agent allocates equal decision weights to given choice alter…
Contextuality and the Weak Axiom in the Theory of Choice
William Zeng, Philipp Zahn
Recent work on the logical structure of non-locality has constructed scenarios where observations of multi-partite systems cannot be adequately described by compositions of non-sig…