1 citations · 1 across the 6 of their papers we have counts for
7 papers · 1 filter
Analog-Friendly Predictive Coding without Activation Derivatives
Francesco Innocenti
Predictive coding (PC) is a local, energy-based alternative to backpropagation (BP) whose iterative inference dynamics make it attractive for implementation on analog hardware. How…
Normative Networks for Source Separation via Local Plasticity and Dendritic Computation
Bariscan Bozkurt, Efe Ali Gorguner, Francesco Innocenti +1
Blind source separation (BSS) is a natural framework for studying how latent causes may be recovered from sensory mixtures, but deriving online and biologically plausible algorithm…
On the Infinite Width and Depth Limits of Predictive Coding Networks
Francesco Innocenti, El Mehdi Achour, Rafal Bogacz
Predictive coding (PC) is a biologically plausible alternative to standard backpropagation (BP) that minimises an energy function with respect to network activities before updating…
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…
Only Strict Saddles in the Energy Landscape of Predictive Coding Networks?
Francesco Innocenti, El Mehdi Achour, Ryan Singh +1
Predictive coding (PC) is an energy-based learning algorithm that performs iterative inference over network activities before updating weights. Recent work suggests that PC can con…