Our article Monte Carlo Graph Search for Quantum Circuit Optimization has been accepted to Physical Review A ( American Physical Society). Details will follow.
We are pleased that our article The voraus-AD Dataset for Anomaly Detection in Robot Applications has been accepted to the IEEE Transactions on Robotics (T-RO). The code and dataset can be accessed here.
Our article Optimization of Sparsity-Constrained Neural Networks as a Mixed Integer Linear Program has been accepted to the Journal of Optimization Theory and Applications (JOTA).
The “Institut für Informationsverarbeitung” (Institute for Information Processing) is the home of machine learning at the Leibniz University Hannover. We focus on three main research directions, namely (I) computer vision & representation learning, (II) signal processing & -coding and (III) automated machine learning. Our methods range from deep learning, automated machine learning, reinforcement learning, image analysis, remote sensing and compression of audio, image, video as well as DNA to biomedical data. Our efforts are directed towards making efficient use of multi-modal and high dimensional data for reliable predictions, ultimately supporting end-users, developers and decision makers in a vast range of applications.
Since the foundation in 1973, the institute holds a strong tradition of cultivating connections to industry partners and jointly developing solutions to automatically process and harness information. Some of the developed methodology were successfully spun-off commercially as for instance with driver assistance modules, cochlear implants or component testing. The institute is also well known for being actively involved in the standardization of MP3, MPEG-2, AVC (H.264), HEVC (H.265) as well as MPEG-G.
Do you want to join us? We have open positions.
