Anand Subramoney
Anand Subramoney
Institut für Neuroinformatik, Ruhr-Universität Bochum
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Cited by
Cited by
Long short-term memory and learning-to-learn in networks of spiking neurons
G Bellec, D Salaj, A Subramoney, R Legenstein, W Maass
Advances in Neural Information Processing Systems 31, 787--797, 2018
A solution to the learning dilemma for recurrent networks of spiking neurons
G Bellec, F Scherr, A Subramoney, E Hajek, D Salaj, R Legenstein, ...
Nature Communications 11 (1), 3625, 2020
Pattern representation and recognition with accelerated analog neuromorphic systems
MA Petrovici, S Schmitt, J Klähn, D Stöckel, A Schroeder, G Bellec, J Bill, ...
2017 IEEE International Symposium on Circuits and Systems (ISCAS), 1-4, 2017
Scaling up liquid state machines to predict over address events from dynamic vision sensors
J Kaiser, R Stal, A Subramoney, A Roennau, R Dillmann
Bioinspiration & biomimetics 12 (5), 055001, 2017
Task decomposition with neuroevolution in extended predator-prey domain
A Jain, A Subramoney, R Miikulainen
The Thirteenth International Conference on the Synthesis and Simulation of …, 2012
Embodied Synaptic Plasticity With Online Reinforcement Learning
J Kaiser, M Hoff, A Konle, JC Vasquez Tieck, D Kappel, D Reichard, ...
Frontiers in Neurorobotics 13, 81, 2019
Reservoirs learn to learn
A Subramoney, F Scherr, W Maass
Reservoir Computing: Theory, Physical Implementations, and Applications., 2020
Spike frequency adaptation supports network computations on temporally dispersed information
D Salaj, A Subramoney, C Kraišniković, G Bellec, R Legenstein, W Maass
bioRxiv, 2020
Eligibility traces provide a data-inspired alternative to backpropagation through time
G Bellec, F Scherr, E Hajek, D Salaj, A Subramoney, R Legenstein, ...
NeurIPS 2019 workshop "Real Neurons & Hidden Units: Future directions at the …, 2019
Evaluating modular neuroevolution in robotic keepaway soccer
A Subramoney
The University of Texas at Austin, 2012
Slow processes of neurons enable a biologically plausible approximation to policy gradient.
A Subramoney, F Scherr, G Bellec, E Hajek, D Salaj, R Legenstein, ...
NeurIPS 2019 workshop on Biological and Artificial Reinforcement Learning, 2019
Learning to Learn on High Performance Computing
A Yegenoglu, W Maas, M Herty, W Klijn, G Visconti, A Subramoney, ...
Society for Neuroscience Meeting 2019, 2019
A normative framework for learning top-down predictions through synaptic plasticity in apical dendrites
A Rao, R Legenstein, A Subramoney, W Maass
bioRxiv, 2021
Revisiting the role of synaptic plasticity and network dynamics for fast learning in spiking neural networks
A Subramoney, G Bellec, F Scherr, R Legenstein, W Maass
bioRxiv, 2021
Spike-frequency adaptation contributes long short-term memory to networks of spiking neurons
A Subramoney, C Kraisnikovic, D Salaj, G Bellec, R Legenstein, W Maass
Bernstein Conference, 2020
IGITUGraz/L2L: L2L Gradient-free Optimization Framework v0.4.3
A Subramoney, A Rao, F Scherr, D Salaj, T Bohnstingl, J Jordan, N Kopp, ..., 2019
IGITUGraz/spore-nest-module: SPORE version 2.14.0
D Kappel, M Hoff, A Subramoney, 2017
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