27 citations · 59 across the 19 of their papers we have counts for
6 papers · 1 filter
Flipped Classroom: Effective Teaching for Time Series Forecasting
Philipp Teutsch, Patrick Mäder
Sequence-to-sequence models based on LSTM and GRU are a most popular choice for forecasting time series data reaching state-of-the-art performance. Training such models can be deli…
Generalizability of Code Clone Detection on CodeBERT
Tim Sonnekalb, Bernd Gruner, Clemens-Alexander Brust +1
Transformer networks such as CodeBERT already achieve outstanding results for code clone detection in benchmark datasets, so one could assume that this task has already been solved…
Dropout is NOT All You Need to Prevent Gradient Leakage
Daniel Scheliga, Patrick Mäder, Marco Seeland
Gradient inversion attacks on federated learning systems reconstruct client training data from exchanged gradient information. To defend against such attacks, a variety of defense…
How Firms Adapt and Interact in Open Source Ecosystems: Analyzing Stakeholder Influence and Collaboration Patterns
Johan Linåker, Patrick Rempel, Björn Regnell +1
[Context and motivation] Ecosystems developed as Open Source Software (OSS) are considered to be highly innovative and reactive to new market trends due to their openness and wide-…
SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection for Autonomous Driving
Sambit Mohapatra, Thomas Mesquida, Mona Hodaei +3
Spiking Neural Networks are a recent and new neural network design approach that promises tremendous improvements in power efficiency, computation efficiency, and processing latenc…
A deep learning approach for direction of arrival estimation using automotive-grade ultrasonic sensors
Mohamed Shawki Elamir, Heinrich Gotzig, Raoul Zoellner +1
In this paper, a deep learning approach is presented for direction of arrival estimation using automotive-grade ultrasonic sensors which are used for driving assistance systems suc…