* marks equal contributions.

2024

Towards Large-scale Network Emulation on Analog Neuromorphic Hardware
Arnold, E., Spilger, P., Straub, J., Müller, E., Dold, D., Meoni, G., Schemmel, J.
arXiv

2023

Artificial Intelligence for Space: AI4SPACE – Trends, Applications, and Perspectives. Chapter: Selected Trends in Artificial Intelligence for Space Applications
Izzo, D., Meoni, G., Gómez, P., Dold, D., Zoechbauer, A.
CRC press, ISBN 9781003366386. arXiv

Artificial Intelligence for Space: AI4SPACE – Trends, Applications, and Perspectives. Chapter: Neuromorphic Computing and Sensing in Space.
Izzo*, D., Hadjiivanov*, A., Dold*, D., Meoni*, G., Blazquez*, E.
CRC press, ISBN 9781003366386. arXiv

Modelling the European Space Sector with Knowledge Graphs.
Berquand*, A., Dold*, D.
German Aerospace Congress 2023.

Differentiable graph-structured models for inverse design of lattice materials.
Dold*, D., Aranguren van Egmond, D.
Cell Reports Physical Science, Volume 4, Issue 10, 101586. arXiv | gitlab | github

Totimorphic structures for space application.
Thomas, A., Grover, J., Izzo, D., Dold, D.
XXVII Italian Association of Aeronautics and Astronautics (AIDAA) Congress. arXiv

A Neuronal Least-Action Principle for Real-Time Learning in Cortical Circuits.
Senn*, W., Dold*, D., Kungl, F., Ellenberger, B., Jordan, J., Bengio, Y., Sacramento, J., Petrovici*, M.
eLife 12:RP89674.

2022

Detection, Explanation and Filtering of Cyber Attacks Combining Symbolic and Sub-Symbolic methods.
Himmelhuber, A., Dold, D., Grimm, S., Zillner, S., Runkler, T.
Computational Intelligence In Cyber Security (IEEE CICS), IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2021). arXiv

Neuro-symbolic computing with spiking neural networks.
Dold, D., Soler Garrido, J., Caceres Chian, V., Hildebrandt and M., Runkler, T.
International Conference on Neuromorphic Systems (ICONS). arXiv

Relational representation learning with spike trains.
Dold, D.
IEEE World Congress on Computational Intelligence (WCCI), International Joint Conference on Neural Networks (IJCNN). arXiv

Evaluating the feasibility of interpretable machine learning for globular cluster detection.
Dold, D. and Fahrion, K.
Astronomy & Astrophysics. arXiv | github

2021

An energy-based model for neuro-symbolic reasoning on knowledge graphs.
Dold, D. and Soler Garrido, J.
20th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA). arXiv

Learning through structure: towards deep neuromorphic knowledge graph embeddings.
Caceres Chian*, V., Hildebrandt*, M., Runkler, T. and Dold*, D.
International Conference on Neuromorphic Computing (ICNC). arXiv

Fast and energy-efficient neuromorphic deep learning with first-spike times.
Göltz*, J., Kriener*, L., Baumbach, A., Billaudelle, S., Breitwieser, O., Cramer, B., Dold, D., ... Petrovici, M. A.
Nature Machine Intelligence, Volume 3. arXiv

Machine learning on knowledge graphs for context-aware security monitoring.
Soler Garrido*, J., Dold*, D. and Frank, J.
IEEE International Conference on Cyber Security and Resilience (IEEE CSR). arXiv | github

SpikE: spike-based embeddings for multi-relational graph data.
Dold, D. and Soler Garrido, J.
International Joint Conference on Neural Networks (IJCNN). arXiv | github

2020

Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate.
Billaudelle*, S., Stradmann*, Y., Schreiber*, K., Cramer*, B., Baumbach*, A., Dold*, D., Göltz*, J., Kungl*, A. F., Wunderlich*, T. C. et al.
2020 IEEE International Symposium on Circuits and Systems (ISCAS), Sevilla, 2020, pp. 1-5. arXiv

2019

Accelerated physical emulation of Bayesian inference in spiking neural networks.
Kungl, A. F., Schmitt, S., Klähn, J., Müller, P., Baumbach, A., Dold, D., ... Kleider, M. et al.
Frontiers in Neuroscience, 13, 1201. arXiv

Stochasticity from function - why the Bayesian brain may need no noise.
Dold*, D., I., Bytschok*, Kungl, A. F., Baumbach, A., Breitwieser, O., Schemmel, J., Meier, K. and Petrovici*, M. A.
Neural Networks, 119, 200-213. arXiv

2017

Spike-based probabilistic inference with correlated noise.
Bytschok*, I., Dold*, D., Schemmel, J., Meier, K. and Petrovici*, M. A.
arXiv

Method and system for anomaly detection in a network.
Europe: EP4270227A1 (28/04/2022). USA: US20230353584A1 (24/04/2023). China: CN116980321A (28/04/2023).

Method and Device for Providing a Recommender System.
Europe: EP4231199A1 (22/02/2022). WIPO: WO2023160947A1 (30/01/2023).

Industrial device and method for building and/or processing a knowledge graph.
Europe: EP4030351A1 (18/01/2021). USA: US20220229400A1 (28/12/2021). China: CN114819049A (18/01/2022)

Neuromorphic hardware for processing a knowledge graph represented by observed triple statements and method for training a learning component.
Europe: EP4030349A1 (18/01/2021). USA: US20220230056A1 (20/12/2021). China: CN114819048A (18/01/2022)

Neuromorphic hardware and method for storing and/or processing a knowledge graph.
Europe: EP4030350A1 (18/01/2021). USA: US20220237441A1 (6/01/2022). China: CN114819047A (18/01/2022).