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cs.LG2024
Continual learning with the neural tangent ensemble
Ari S. Benjamin, Christian Pehle, Kyle Daruwalla
A natural strategy for continual learning is to weigh a Bayesian ensemble of fixed functions. This suggests that if a (single) neural network could be interpreted as an ensemble, o…
cs.NE2024
jaxsnn: Event-driven Gradient Estimation for Analog Neuromorphic Hardware
Eric Müller, Moritz Althaus, Elias Arnold +3
Traditional neuromorphic hardware architectures rely on event-driven computation, where the asynchronous transmission of events, such as spikes, triggers local computations within…