Andrew Sornborger
3 papers in the PaperMetrix corpus
Papers by this author
-
Out-of-distribution generalization for learning quantum dynamics
2022 · arXiv (Cornell University)
Generalization bounds are a critical tool to assess the training data requirements of Quantum Machine Learning (QML). Recent work has established guarantees for in-distribution generalization of quantum neural networks (QNNs), where training and testing data …
-
A Neuromorphic Normalization Algorithm for Stabilizing Synaptic Weights with Application to Dictionary Learning in LCA
2022
Instabilities in neuromorphic machine learning can occur when synaptic updates meant to encode matrix transforms are not normalized. This phenomenon is encountered in Hebbian learning [5], where, as a synapse’s strength grows, post-synaptic activity increases, …
-
Neuromorphic on-chip reservoir computing with spiking neural network architectures
2024 · arXiv (Cornell University)
Reservoir computing is a promising approach for harnessing the computational power of recurrent neural networks while dramatically simplifying training. This paper investigates the application of integrate-and-fire neurons within reservoir computing frameworks for two distinct tasks: …