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 | 532 | 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 | 458 | 2020 |
Spike frequency adaptation supports network computations on temporally dispersed information D Salaj*, A Subramoney*, C Kraisnikovic*, G Bellec, R Legenstein, ... Elife 10, e65459, 2021 | 60* | 2021 |
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 | 28 | 2017 |
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 | 23 | 2017 |
Reservoirs learn to learn A Subramoney, F Scherr, W Maass Reservoir Computing: Theory, Physical Implementations, and Applications., 2020 | 22 | 2020 |
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 | 17 | 2019 |
Efficient recurrent architectures through activity sparsity and sparse back-propagation through time A Subramoney, KK Nazeer, M Schöne, C Mayr, D Kappel The Eleventh International Conference on Learning Representations, 2023 | 16 | 2023 |
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 | 10 | 2012 |
Exploring parameter and hyper-parameter spaces of neuroscience models on high performance computers with Learning to Learn A Yegenoglu, A Subramoney, T Hater, C Jimenez-Romero, W Klijn, ... Frontiers in Computational Neuroscience, 46, 2022 | 9 | 2022 |
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 | 9 | 2019 |
Beyond Weights: Deep learning in Spiking Neural Networks with pure synaptic-delay training E Grappolini, A Subramoney Proceedings of the 2023 International Conference on Neuromorphic Systems, 1-4, 2023 | 4 | 2023 |
Language Modeling on a SpiNNaker 2 Neuromorphic Chip KK Nazeer, M Schöne, R Mukherji, B Vogginger, C Mayr, D Kappel, ... arXiv preprint arXiv:2312.09084, 2023 | 3 | 2023 |
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, 2021.01. 25.428153, 2021 | 3 | 2021 |
Igitugraz/l2l: v1.0.0-beta, March 2019 A Subramoney, S Diaz-Pier, A Rao, F Scherr, D Salaj, T Bohnstingl, ... https://doi.org/10.5281/zenodo 2590760, 0 | 3 | |
Activity sparsity complements weight sparsity for efficient RNN inference R Mukherji, M Schöne, KK Nazeer, C Mayr, A Subramoney arXiv preprint arXiv:2311.07625, 2023 | 2 | 2023 |
Block-local learning with probabilistic latent representations D Kappel, KK Nazeer, CT Fokam, C Mayr, A Subramoney arXiv preprint arXiv:2305.14974, 2023 | 2 | 2023 |
Efficient Real Time Recurrent Learning through combined activity and parameter sparsity A Subramoney ICLR 2023 Workshop on Sparsity in Neural Networks, 2023 | 2 | 2023 |
Evaluating modular neuroevolution in robotic keepaway soccer A Subramoney The University of Texas at Austin, 2012 | 2 | 2012 |
Self-supervised learning of probabilistic prediction through synaptic plasticity in apical dendrites: A normative model A Rao, R Legenstein, A Subramoney, W Maass | 1 | 2021 |