1 citations · 1 across the 2 of their papers we have counts for
4 papers
A Simple Generalisation of the Implicit Dynamics of In-Context Learning
Francesco Innocenti, El Mehdi Achour
In-context learning (ICL) refers to the ability of a model to learn new tasks from examples in its input without any parameter updates. In contrast to previous theories of ICL rely…
Towards Scaling Deep Neural Networks with Predictive Coding: Theory and Practice
Francesco Innocenti
Backpropagation (BP) is the standard algorithm for training the deep neural networks that power modern artificial intelligence including large language models. However, BP is energ…
PC: Scaling Predictive Coding to 100+ Layer Networks
Francesco Innocenti, El Mehdi Achour, Christopher L. Buckley
The biological implausibility of backpropagation (BP) has motivated many alternative, brain-inspired algorithms that attempt to rely only on local information, such as predictive c…
JPC: Flexible Inference for Predictive Coding Networks in JAX
Francesco Innocenti, Paul Kinghorn, Will Yun-Farmbrough +3
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) inc…