Training dynamically balanced excitatory-inhibitory networks

29 December 2018

Papers citing "Training dynamically balanced excitatory-inhibitory networks"

9 / 9 papers shown

Title
Learning fast changing slow in spiking neural networks Cristiano Capone P. Muratore OffRL 50 0 0 25 Jan 2024
Approximating nonlinear functions with latent boundaries in low-rank excitatory-inhibitory spiking networks William F. Podlaski C. Machens 59 10 0 18 Jul 2023
A Study of Biologically Plausible Neural Network: The Role and Interactions of Brain-Inspired Mechanisms in Continual Learning F. Sarfraz Elahe Arani Bahram Zonooz 62 3 0 13 Apr 2023
MAP-SNN: Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks Chengting Yu Yang-Guang Du Mufeng Chen Aili Wang Gaoang Wang Erping Li AAML 95 3 0 21 Apr 2022
Input correlations impede suppression of chaos and learning in balanced rate networks Rainer Engelken Alessandro Ingrosso Ramin Khajeh Sven Goedeke L. F. Abbott 68 14 0 24 Jan 2022
Exploring Flip Flop memories and beyond: training recurrent neural networks with key insights C. Jarne 35 0 0 15 Oct 2020
Optimal Learning with Excitatory and Inhibitory synapses Alessandro Ingrosso 41 5 0 25 May 2020
Thalamo-cortical spiking model of incremental learning combining perception, context and NREM-sleep-mediated noise-resilience B. Golosio Chiara De Luca C. Capone E. Pastorelli G. Stegel Gianmarco Tiddia G. Bonis P. Paolucci CLL 64 21 0 26 Mar 2020
Balanced Excitation and Inhibition are Required for High-Capacity, Noise-Robust Neuronal Selectivity Ran Rubin L. F. Abbott H. Sompolinsky 46 107 0 03 May 2017