Follow
Dominik Dold
Dominik Dold
Research Fellow, ESA ESTEC
Verified email at esa.int - Homepage
Title
Cited by
Cited by
Year
Fast and energy-efficient neuromorphic deep learning with first-spike times
J Göltz, L Kriener, A Baumbach, S Billaudelle, O Breitwieser, B Cramer, ...
Nature machine intelligence 3 (9), 823-835, 2021
154*2021
Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate
S Billaudelle, Y Stradmann, K Schreiber, B Cramer, A Baumbach, D Dold, ...
2020 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2020
602020
Accelerated physical emulation of bayesian inference in spiking neural networks
AF Kungl, S Schmitt, J Klähn, P Müller, A Baumbach, D Dold, A Kugele, ...
Frontiers in neuroscience 13, 1201, 2019
49*2019
Stochasticity from function—why the bayesian brain may need no noise
D Dold, I Bytschok, AF Kungl, A Baumbach, O Breitwieser, W Senn, ...
Neural networks 119, 200-213, 2019
36*2019
Machine learning on knowledge graphs for context-aware security monitoring
JS Garrido, D Dold, J Frank
2021 IEEE International Conference on Cyber Security and Resilience (CSR), 55-60, 2021
292021
A neuronal least-action principle for real-time learning in cortical circuits
W Senn, D Dold, AF Kungl, B Ellenberger, J Jordan, Y Bengio, ...
ELife 12, RP89674, 2024
23*2024
Differentiable graph-structured models for inverse design of lattice materials
D Dold, DA van Egmond
Cell Reports Physical Science 4 (10), 2023
162023
Selected Trends in Artificial Intelligence for Space Applications
D Izzo, G Meoni, P Gómez, D Dold, A Zoechbauer
arXiv preprint arXiv:2212.06662, 2022
152022
Neuromorphic Computing and Sensing in Space
D Izzo, A Hadjiivanov, D Dold, G Meoni, E Blazquez
arXiv preprint arXiv:2212.05236, 2022
132022
Learning through structure: towards deep neuromorphic knowledge graph embeddings
VC Chian, M Hildebrandt, T Runkler, D Dold
2021 International Conference on Neuromorphic Computing (ICNC), 61-70, 2021
132021
An energy-based model for neuro-symbolic reasoning on knowledge graphs
D Dold, JS Garrido
2021 20th IEEE International Conference on Machine Learning and Applications …, 2021
112021
Spike: Spike-based embeddings for multi-relational graph data
D Dold, JS Garrido
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
102021
Detection, Explanation and Filtering of Cyber Attacks Combining Symbolic and Sub-Symbolic Methods
A Himmelhuber, D Dold, S Grimm, S Zillner, T Runkler
2022 IEEE Symposium Series on Computational Intelligence (SSCI), 381-388, 2022
92022
Neuro-symbolic computing with spiking neural networks
D Dold, J Soler Garrido, V Caceres Chian, M Hildebrandt, T Runkler
Proceedings of the International Conference on Neuromorphic Systems 2022, 1-4, 2022
82022
Relational representation learning with spike trains
D Dold
2022 International Joint Conference on Neural Networks (IJCNN), 2022
42022
Evaluating the feasibility of interpretable machine learning for globular cluster detection
D Dold, K Fahrion
Astronomy & Astrophysics (A&A) 663, A81, 2022
32022
Deep reinforcement learning in a time-continuous model
AF Kungl, D Dold, O Riedler, W Senn, MA Petrovici
Bernstein Conference, 2019
3*2019
Harnessing function from form: towards bio-inspired artificial intelligence in neuronal substrates
D Dold
22020
Advance Concepts Team
D Izzo
European Space Agency, 2004
22004
Method and system for anomaly detection in a network
Y Liu, M Joblin, M Hildebrandt, D Dold
US Patent App. 18/138,197, 2023
12023
The system can't perform the operation now. Try again later.
Articles 1–20