Dominik Dold

35 papers B 2C 3Misc 1Journal 25Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Equivalence of approximation by networks of single- and multi-spike neurons.
CoRR
Dominik Dold, Philipp Christian Petersen
2025 J jnl
Causal pieces: analysing and improving spiking neural networks piece by piece.
CoRR
Dominik Dold, Philipp Christian Petersen
2025 J jnl
Decentralised self-organisation of pivoting cube ensembles using geometric deep learning.
CoRR
Nadezhda Dobreva, Emmanuel Blazquez, Jai Grover, Dario Izzo, Yuzhen Qin, Dominik Dold
2025 J jnl
Energy efficiency analysis of Spiking Neural Networks for space applications.
CoRR
Paolo Lunghi, Stefano Silvestrini, Dominik Dold, Gabriele Meoni, Alexander Hadjiivanov, Dario Izzo
2025 J jnl
Guidance and Control Neural Network Acceleration using Memristors.
CoRR
Zacharia Rudge, Dario Izzo, Moritz Fieback, Anteneh Gebregiorgis, Said Hamdioui, Dominik Dold
2025 J jnl
Memristor-Based Neural Network Accelerators for Space Applications: Enhancing Performance with Temporal Averaging and SIRENs.
CoRR
Zacharia Rudge, Dominik Dold, Moritz Fieback, Dario Izzo, Said Hamdioui
2025 J jnl
Stable learning using spiking neural networks equipped with affine encoders and decoders.
J. Mach. Learn. Res.
A. Martina Neuman, Dominik Dold, Philipp Christian Petersen
2024 J jnl
Continuous Design and Reprogramming of Totimorphic Structures for Space Applications.
CoRR
Dominik Dold, Amy Thomas, Nicole Rosi, Jai Grover, Dario Izzo
2024 — conf
The Space Optimization Competition: Third Edition.
GECCO Companion
Max Bannach, Emmanuel Blazquez, Dario Izzo, Giacomo Acciarini, Alexander Hadjiivanov, Gernot Heißel, Rita Mastroianni, Sebastien Origer, Jai Grover, Dominik Dold, Zacharia Rudge
2024 J jnl
Towards Large-scale Network Emulation on Analog Neuromorphic Hardware.
CoRR
Elias Arnold, Philipp Spilger, Jan V. Straub, Eric Müller, Dominik Dold, Gabriele Meoni, Johannes Schemmel
2023 J jnl
Differentiable graph-structured models for inverse design of lattice materials.
CoRR
Dominik Dold, Derek Aranguren van Egmond
2022 — conf
Detection, Explanation and Filtering of Cyber Attacks Combining Symbolic and Sub-Symbolic Methods.
SSCI
Anna Himmelhuber, Dominik Dold, Stephan Grimm, Sonja Zillner, Thomas A. Runkler
2022 J jnl
Detection, Explanation and Filtering of Cyber Attacks Combining Symbolic and Sub-Symbolic Methods.
CoRR
Anna Himmelhuber, Dominik Dold, Stephan Grimm, Sonja Zillner, Thomas A. Runkler
2022 — conf
Neuro-symbolic computing with spiking neural networks.
ICONS
Dominik Dold, Josep Soler Garrido, Victor Caceres Chian, Marcel Hildebrandt, Thomas A. Runkler
2022 J jnl
Neuro-symbolic computing with spiking neural networks.
CoRR
Dominik Dold, Josep Soler Garrido, Victor Caceres Chian, Marcel Hildebrandt, Thomas A. Runkler
2022 J jnl
Neuromorphic Computing and Sensing in Space.
CoRR
Dario Izzo, Alexander Hadjiivanov, Dominik Dold, Gabriele Meoni, Emmanuel Blazquez
2022 B conf
Relational representation learning with spike trains.
IJCNN
Dominik Dold
2022 J jnl
Relational representation learning with spike trains.
CoRR
Dominik Dold
2022 J jnl
Selected Trends in Artificial Intelligence for Space Applications.
CoRR
Dario Izzo, Gabriele Meoni, Pablo Gómez, Dominik Dold, Alexander Zoechbauer
2021 C conf
An energy-based model for neuro-symbolic reasoning on knowledge graphs.
ICMLA
Dominik Dold, Josep Soler Garrido
2021 J jnl
An energy-based model for neuro-symbolic reasoning on knowledge graphs.
CoRR
Dominik Dold, Josep Soler Garrido
2021 J jnl
Fast and energy-efficient neuromorphic deep learning with first-spike times.
Nat. Mach. Intell.
Julian Göltz, Laura Kriener, Andreas Baumbach, Sebastian Billaudelle, Oliver Breitwieser, Benjamin Cramer, Dominik Dold, Ákos F. Kungl, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
2021 J jnl
Learning through structure: towards deep neuromorphic knowledge graph embeddings.
CoRR
Victor Caceres Chian, Marcel Hildebrandt, Thomas A. Runkler, Dominik Dold
2021 Misc conf
Machine learning on knowledge graphs for context-aware security monitoring.
CSR
Josep Soler Garrido, Dominik Dold, Johannes Frank
2021 J jnl
Machine learning on knowledge graphs for context-aware security monitoring.
CoRR
Josep Soler Garrido, Dominik Dold, Johannes Frank
2021 B conf
SpikE: spike-based embeddings for multi-relational graph data.
IJCNN
Dominik Dold, Josep Soler Garrido
2021 J jnl
SpikE: spike-based embeddings for multi-relational graph data.
CoRR
Dominik Dold, Josep Soler Garrido
2020 — —
Harnessing function from form: towards bio-inspired artificial intelligence in neuronal substrates
Dominik Dold
2020 C conf
Live Demonstration: Versatile Emulation of Spiking Neural Networks on an Accelerated Neuromorphic Substrate.
ISCAS
Sebastian Billaudelle, Yannik Stradmann, Korbinian Schreiber, Benjamin Cramer, Andreas Baumbach, Dominik Dold, Julian Göltz, Ákos Ferenc Kungl, Timo C. Wunderlich, Andreas Hartel, Eric Müller, Oliver Breitwieser, Christian Mauch, Mitja Kleider, Andreas Grübl, David Stöckel, Christian Pehle, Arthur Heimbrecht, Philipp Spilger, Gerd Kiene, Vitali Karasenko, Walter Senn, Mihai A. Petrovici, Johannes Schemmel, Karlheinz Meier
2020 C conf
Versatile Emulation of Spiking Neural Networks on an Accelerated Neuromorphic Substrate.
ISCAS
Sebastian Billaudelle, Yannik Stradmann, Korbinian Schreiber, Benjamin Cramer, Andreas Baumbach, Dominik Dold, Julian Göltz, Ákos Ferenc Kungl, Timo C. Wunderlich, Andreas Hartel, Eric Müller, Oliver Breitwieser, Christian Mauch, Mitja Kleider, Andreas Grübl, David Stöckel, Christian Pehle, Arthur Heimbrecht, Philipp Spilger, Gerd Kiene, Vitali Karasenko, Walter Senn, Mihai A. Petrovici, Johannes Schemmel, Karlheinz Meier
2019 J jnl
Fast and deep neuromorphic learning with time-to-first-spike coding.
CoRR
Julian Göltz, Andreas Baumbach, Sebastian Billaudelle, Oliver Breitwieser, Dominik Dold, Laura Kriener, Ákos Ferenc Kungl, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
2019 J jnl
Stochasticity from function - Why the Bayesian brain may need no noise.
Neural Networks
Dominik Dold, Ilja Bytschok, Ákos F. Kungl, Andreas Baumbach, Oliver Breitwieser, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
2019 J jnl
Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate.
CoRR
Sebastian Billaudelle, Yannik Stradmann, Korbinian Schreiber, Benjamin Cramer, Andreas Baumbach, Dominik Dold, Julian Göltz, Ákos F. Kungl, Timo C. Wunderlich, Andreas Hartel, Eric Müller, Oliver Breitwieser, Christian Mauch, Mitja Kleider, Andreas Grübl, David Stöckel, Christian Pehle, Arthur Heimbrecht, Philipp Spilger, Gerd Kiene, Vitali Karasenko, Walter Senn, Mihai A. Petrovici, Johannes Schemmel, Karlheinz Meier
2018 J jnl
Generative models on accelerated neuromorphic hardware.
CoRR
Ákos F. Kungl, Sebastian Schmitt, Johann Klähn, Paul Müller, Andreas Baumbach, Dominik Dold, Alexander Kugele, Nico Gürtler, Luziwei Leng, Eric Müller, Christoph Koke, Mitja Kleider, Christian Mauch, Oliver Breitwieser, Maurice Güttler, Dan Husmann de Oliveira, Kai Husmann, Joscha Ilmberger, Andreas Hartel, Vitali Karasenko, Andreas Grübl, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
2018 J jnl
Stochasticity from function - why the Bayesian brain may need no noise.
CoRR
Dominik Dold, Ilja Bytschok, Ákos F. Kungl, Andreas Baumbach, Oliver Breitwieser, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici