Predicting non-linear dynamics: a stable local learning scheme for recurrent spiking neural networks. - Aditya Gilra; Wulfram Gerstner (CoRR, 2017)

Multi-timescale memory dynamics in a reinforcement learning network with attention-gated memory. - Marco Martinolli; Wulfram Gerstner; Aditya Gilra (CoRR, 2017)

Non-Linear Motor Control by Local Learning in Spiking Neural Networks. - Aditya Gilra; Wulfram Gerstner (ICML, 2018)

Multi-Timescale Memory Dynamics Extend Task Repertoire in a Reinforcement Learning Network With Attention-Gated Memory. - Marco Martinolli; Wulfram Gerstner; Aditya Gilra (Frontiers Comput. Neurosci., 2018)

NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. - Jason Yik; Soikat Hasan Ahmed; Zergham Ahmed; Brian Anderson; Andreas G. Andreou; Chiara Bartolozzi; Arindam Basu; Douwe den Blanken; Petrut Bogdan; Sander M. Bohté; Younes Bouhadjar; Sonia M. Buckley; et al. (CoRR, 2023)

Modelling novelty detection in the thalamocortical loop. - Chao Han; Gwendolyn English; Hannes P. Saal; Giacomo Indiveri; Aditya Gilra; Wolfger von der Behrens; Eleni Vasilaki (PLoS Comput. Biol., 2023)

Measuring Exploration in Reinforcement Learning via Optimal Transport in Policy Space. - Reabetswe M. Nkhumise; Debabrota Basu; Tony J. Prescott; Aditya Gilra (CoRR, 2024)

Dynamical-VAE-based Hindsight to Learn the Causal Dynamics of Factored-POMDPs. - Chao Han; Debabrota Basu; Michael Mangan; Eleni Vasilaki; Aditya Gilra (CoRR, 2024)

Studying Exploration in RL: An Optimal Transport Analysis of Occupancy Measure Trajectories. - Reabetswe M. Nkhumise; Debabrota Basu; Tony J. Prescott; Aditya Gilra (Trans. Mach. Learn. Res., 2025)

Lagrangian-based Equilibrium Propagation: generalisation to arbitrary boundary conditions & equivalence with Hamiltonian Echo Learning. - Guillaume Pourcel; Debabrota Basu; Maxence Ernoult; Aditya Gilra (CoRR, 2025)