* marks equal contributions.

2024

Energy efficiency analysis of Spiking Neural Networks based on temporal coding for space applications
P. Lunghi, S. Silvestrini, D. Dold, G. Meoni, A. Hadjiivanov, D. Izzo.
Submitted. Under review.

Proceedings of SPAICE2024: The First Joint European Space Agency / IAA Conference on AI in and for Space.
Editors: D. Dold, A. Hadjiivanov, D. Izzo.

Guidance and Control Neural Network Acceleration using Memristors
Z. A. Rudge, D. Izzo, M. Fieback, A. Gebregiorgis, S. Hamdioui, D. Dold
Proceedings of SPAICE2024: The First Joint European Space Agency/IAA Conference on AI in and for Space (pp. 162-168).

Lost in space but not in data: Tracking Technology Trends in the Space Field
A. Berquand, A. V. Ladeira, D. Dold
Proceedings of SPAICE2024: The First Joint European Space Agency/IAA Conference on AI in and for Space (pp. 145-149).

The Space Optimization Competition: Third Edition
M. Bannach, E. Blazquez, D. Izzo, G. Acciarini, A. Hadjiivanov, G. Heißel, R. Mastroianni, S. Origer, J. Grover, D. Dold, Z. Rudge
The Genetic and Evolutionary Computation Conference (GECCO). github

Towards Large-scale Network Emulation on Analog Neuromorphic Hardware
E. Arnold, P. Spilger, J. Straub, E. Müller, D. Dold, G. Meoni, J. Schemmel
Neuro Inspired Computational Elements Conference (NICE 2024). arXiv

2023

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

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

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

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

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

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

2022

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

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

Relational representation learning with spike trains.
D. Dold
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.
D. Dold*, K. Fahrion*
Astronomy & Astrophysics. arXiv | github

2021

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

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

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

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

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

2020

Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate.
S. Billaudelle*, Y. Stradmann*, K. Schreiber*, B. Cramer*, A. Baumbach*, D. Dold*, J. Göltz*, A. F. Kungl*, T. C. Wunderlich*, 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.
A. F. Kungl, S. Schmitt, J. Klähn, P. Müller, A. Baumbach, D. Dold, ... M. Kleider, et al.
Frontiers in Neuroscience, 13, 1201. arXiv

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

2017

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