Task decomposition with neuroevolution in extended predator-prey domain. - Ashish Jain; Anand Subramoney; Risto Miikkulainen (ALIFE, 2012)

Pattern representation and recognition with accelerated analog neuromorphic systems. - Mihai A. Petrovici; Sebastian Schmitt; Johann Klähn; Robert D. St. Louis; Anna Schroeder; Guillaume Bellec; Johannes Bill; Oliver Breitwieser; Ilja Bytschok; Andreas Grübl; Maurice Güttler; Andreas Hartel; et al. (ISCAS, 2017)

Pattern representation and recognition with accelerated analog neuromorphic systems. - Mihai A. Petrovici; Sebastian Schmitt; Johann Klähn; David Stöckel; Anna Schroeder; Guillaume Bellec; Johannes Bill; Oliver Breitwieser; Ilja Bytschok; Andreas Grübl; Maurice Güttler; Andreas Hartel; et al. (CoRR, 2017)

Long short-term memory and Learning-to-learn in networks of spiking neurons. - Guillaume Bellec; Darjan Salaj; Anand Subramoney; Robert Legenstein; Wolfgang Maass 001 (NeurIPS, 2018)

Reservoirs learn to learn. - Anand Subramoney; Franz Scherr; Wolfgang Maass 001 (CoRR, 2019)

Embodied Synaptic Plasticity With Online Reinforcement Learning. - Jacques Kaiser; Michael Hoff 001; Andreas Konle; Juan Camilo Vasquez Tieck; David Kappel; Daniel Reichard; Anand Subramoney; Robert Legenstein; Arne Roennau; Wolfgang Maass 001; Rüdiger Dillmann (Frontiers Neurorobotics, 2019)

Reservoirs Learn to Learn. - Anand Subramoney; Franz Scherr; Wolfgang Maass 001 (Reservoir Computing, 2021)

Exploring hyper-parameter spaces of neuroscience models on high performance computers with Learning to Learn. - Alper Yegenoglu; Anand Subramoney; Thorsten Hater; Cristian Jimenez-Romero; Wouter Klijn; Aaron Perez Martin; Michiel van der Vlag; Michael Herty; Abigail Morrison; Sandra Diaz-Pier (CoRR, 2022)

EGRU: Event-based GRU for activity-sparse inference and learning. - Anand Subramoney; Khaleelulla Khan Nazeer; Mark Schöne; Christian Mayr 001; David Kappel (CoRR, 2022)

Exploring Parameter and Hyper-Parameter Spaces of Neuroscience Models on High Performance Computers With Learning to Learn. - Alper Yegenoglu; Anand Subramoney; Thorsten Hater; Cristian Jimenez-Romero; Wouter Klijn; Aaron Perez Martin; Michiel van der Vlag; Michael Herty; Abigail Morrison; Sandra Diaz-Pier (Frontiers Comput. Neurosci., 2022)

Efficient recurrent architectures through activity sparsity and sparse back-propagation through time. - Anand Subramoney; Khaleelulla Khan Nazeer; Mark Schöne; Christian Mayr 001; David Kappel (ICLR, 2023)

Beyond Weights: Deep learning in Spiking Neural Networks with pure synaptic-delay training. - Edoardo W. Grappolini; Anand Subramoney (ICONS, 2023)

Efficient Real Time Recurrent Learning through combined activity and parameter sparsity. - Anand Subramoney (CoRR, 2023)

Block-local learning with probabilistic latent representations. - David Kappel; Khaleelulla Khan Nazeer; Cabrel Teguemne Fokam; Christian Mayr 001; Anand Subramoney (CoRR, 2023)

Activity Sparsity Complements Weight Sparsity for Efficient RNN Inference. - Rishav Mukherji; Mark Schöne; Khaleelulla Khan Nazeer; Christian Mayr 001; Anand Subramoney (CoRR, 2023)

Language Modeling on a SpiNNaker 2 Neuromorphic Chip. - Khaleelulla Khan Nazeer; Mark Schöne; Rishav Mukherji; Christian Mayr 001; David Kappel; Anand Subramoney (CoRR, 2023)

Language Modeling on a SpiNNaker2 Neuromorphic Chip. - Khaleelulla Khan Nazeer; Mark Schöne; Rishav Mukherji; Bernhard Vogginger; Christian Mayr 001; David Kappel; Anand Subramoney (AICAS, 2024)

Weight Sparsity Complements Activity Sparsity in Neuromorphic Language Models. - Rishav Mukherji; Mark Schöne; Khaleelulla Khan Nazeer; Christian Mayr 001; David Kappel; Anand Subramoney (ICONS, 2024)

Scalable Event-by-Event Processing of Neuromorphic Sensory Signals with Deep State-Space Models. - Mark Schöne; Neeraj Mohan Sushma; Jingyue Zhuge; Christian Mayr 001; Anand Subramoney; David Kappel (ICONS, 2024)

Exploring the limits of Hierarchical World Models in Reinforcement Learning. - Robin Schiewer; Anand Subramoney; Laurenz Wiskott (CoRR, 2024)

Asynchronous Stochastic Gradient Descent with Decoupled Backpropagation and Layer-Wise Updates. - Cabrel Teguemne Fokam; Khaleelulla Khan Nazeer; Lukas König; David Kappel; Anand Subramoney (CoRR, 2024)

State-space models can learn in-context by gradient descent. - Neeraj Mohan Sushma; Yudou Tian; Harshvardhan Mestha; Nicolò Colombo; David Kappel; Anand Subramoney (CoRR, 2024)

STREAM: A Universal State-Space Model for Sparse Geometric Data. - Mark Schöne; Yash Bhisikar; Karan Bania; Khaleelulla Khan Nazeer; Christian Mayr 001; Anand Subramoney; David Kappel (CoRR, 2024)

Efficient large language model with analog in-memory computing. - Anand Subramoney (Nat. Comput. Sci., 2025)