8 citations · 9 across the 4 of their papers we have counts for
4 papers
A Sparse Quantized Hopfield Network for Online-Continual Memory
Nick Alonso, Jeff Krichmar
An important difference between brains and deep neural networks is the way they learn. Nervous systems learn online where a stream of noisy data points are presented in a non-indep…
Understanding and Improving Optimization in Predictive Coding Networks
Nick Alonso, Jeff Krichmar, Emre Neftci
Backpropagation (BP), the standard learning algorithm for artificial neural networks, is often considered biologically implausible. In contrast, the standard learning algorithm for…
A Theoretical Framework for Inference Learning
Nick Alonso, Beren Millidge, Jeff Krichmar +1
Backpropagation (BP) is the most successful and widely used algorithm in deep learning. However, the computations required by BP are challenging to reconcile with known neurobiolog…
Tightening the Biological Constraints on Gradient-Based Predictive Coding
Nick Alonso, Emre Neftci
Predictive coding (PC) is a general theory of cortical function. The local, gradient-based learning rules found in one kind of PC model have recently been shown to closely approxim…