737 citations
- Universität UlmDE65 papers
- Helmholtz-Institute UlmDE7 papers
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)DE5 papers
- Laboratoire d'Informatique, de Robotique et de Microélectronique de MontpellierFR3 papers
- Robert Bosch (Netherlands)NL3 papers
- Technical University of DenmarkDK3 papers
- University of CambridgeGB3 papers
- Center for Integrated Quantum Science and TechnologyDE2 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- École de management de LyonFR2 papers
- Jet Propulsion LaboratoryUS2 papers
- Robert Bosch (Germany)DE2 papers
8 papers · 1 filter
Electricity Price Prediction Using Multi-Kernel Gaussian Process Regression Combined with Kernel-Based Support Vector Regression
Abhinav Das, Stephan Schlüter, Lorenz Schneider
This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian Process Regression (GPR) and Support Vector Reg…
IMUDiffusion: A Diffusion Model for Multivariate Time Series Synthetisation for Inertial Motion Capturing Systems
Heiko Oppel, Michael Munz
Kinematic sensors are often used to analyze movement behaviors in sports and daily activities due to their ease of use and lack of spatial restrictions, unlike video-based motion c…
Boosted Bell-state measurements for photonic quantum computation
Nico Hauser, Matthias J. Bayerbach, Simone E. D'Aurelio +5
Fault-tolerant fusion-based photonic quantum computing (FBQC) greatly relies on entangling two-photon measurements, called fusions. These fusions can be realized using linear-optic…
Less is More: Selective Reduction of CT Data for Self-Supervised Pre-Training of Deep Learning Models with Contrastive Learning Improves Downstream Classification Performance
Daniel Wolf, Tristan Payer, Catharina Silvia Lisson +4
Self-supervised pre-training of deep learning models with contrastive learning is a widely used technique in image analysis. Current findings indicate a strong potential for contra…
Optimal Control of a Battery Storage On the Energy Market
Stephan Schlüter, Abhinav Das, Mathew Davison
Electricity storage is crucial for a successful transition towards carbon-neutral energy production. Despite considerable research and a number of promising future alternatives suc…
Generating Synthetic Rainfall Fields by R-vine Copulas Applied to Seamless Probabilistic Predictions
Peter Schaumann, Martin Rempel, Ulrich Blahak +1
Many post-processing methods improve forecasts at individual locations but remove their correlation structure, which is crucial for predicting larger-scale events like total precip…