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Damien Querlioz

2 accepted papers

2026

Active Continual Learning with Metaplastic Binary Bayesian Neural Networks

ICML 2026poster

Always-on edge systems must keep learning as conditions change under tight compute budgets and must detect unreliable predictions. Bayesian binary neural networks are attractive in this setting, but mean-field Bernoulli posteriors can saturate on long non-stationary streams, wiping out epistemic unc…

Cited by 0SourceScholar
2019

Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input

NeurIPS 2019oral

Equilibrium Propagation (EP) is a biologically inspired learning algorithm for convergent recurrent neural networks, i.e. RNNs that are fed by a static input x and settle to a steady state. Training convergent RNNs consists in adjusting the weights until the steady state of output neurons coincides…