302 citations · 306 across the 6 of their papers we have counts for
7 papers · 1 filter
Vision Hopfield Memory Networks for Image Recognition
Jianfeng Wang, Amine M'Charrak, Luk Koska +6
Recent vision backbones, such as Transformer families and state-space models like Mamba, have achieved remarkable progress on image recognition. Despite their empirical success, th…
Faster Predictive Coding Networks via Better Initialization
Luca Pinchetti, Simon Frieder, Thomas Lukasiewicz +1
Research aimed at scaling up neuroscience inspired learning algorithms for neural networks is accelerating. Recently, a key research area has been the study of energy-based learnin…
Benchmarking Predictive Coding Networks -- Made Simple
Luca Pinchetti, Chang Qi, Oleh Lokshyn +9
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, called PCX, that focus…
Predictive Coding beyond Correlations
Tommaso Salvatori, Luca Pinchetti, Amine M'Charrak +2
Recently, there has been extensive research on the capabilities of biologically plausible algorithms. In this work, we show how one of such algorithms, called predictive coding, is…
Mathematical Capabilities of ChatGPT
Simon Frieder, Luca Pinchetti, Alexis Chevalier +5
We investigate the mathematical capabilities of two iterations of ChatGPT (released 9-January-2023 and 30-January-2023) and of GPT-4 by testing them on publicly available datasets,…
Predictive Coding beyond Gaussian Distributions
Luca Pinchetti, Tommaso Salvatori, Yordan Yordanov +3
A large amount of recent research has the far-reaching goal of finding training methods for deep neural networks that can serve as alternatives to backpropagation (BP). A prominent…