Benchmarking Predictive Coding Networks--Made Simple
In this work, we tackle the problems of efficiency and scalability for predictive coding
networks in machine learning. To do so, we first propose a library called PCX, whose focus …
networks in machine learning. To do so, we first propose a library called PCX, whose focus …
JPC: Flexible Inference for Predictive Coding Networks in JAX
We introduce JPC, a JAX library for training neural networks with Predictive Coding. JPC
provides a simple, fast and flexible interface to train a variety of PC networks (PCNs) …
provides a simple, fast and flexible interface to train a variety of PC networks (PCNs) …
Confidence and second-order errors in cortical circuits
Minimization of cortical prediction errors has been considered a key computational goal of
the cerebral cortex underlying perception, action, and learning. However, it is still unclear …
the cerebral cortex underlying perception, action, and learning. However, it is still unclear …
Neuron-level prediction and noise can implement flexible reward-seeking behavior
We show that neural networks can implement reward-seeking behavior using only local
predictive updates and internal noise. These networks are capable of autonomous …
predictive updates and internal noise. These networks are capable of autonomous …
BENCHMARKING PREDICTIVE CODING NETWORKS–MADE SIMPLE
M SIMPLE - openreview.net
In this work, we tackle the problems of efficiency and scalability for predictive coding
networks (PCNs) in machine learning. To do so, we propose a library that focuses on …
networks (PCNs) in machine learning. To do so, we propose a library that focuses on …