31 citations · 57 across the 8 of their papers we have counts for
10 papers
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…
Towards the Training of Deeper Predictive Coding Neural Networks
Chang Qi, Matteo Forasassi, Thomas Lukasiewicz +1
Predictive coding networks are neural models that perform inference through an iterative energy minimization process, whose operations are local in space and time. While effective…
Tight Stability, Convergence, and Robustness Bounds for Predictive Coding Networks
Ankur Mali, Tommaso Salvatori, Alexander Ororbia
Energy-based learning algorithms, such as predictive coding (PC), have garnered significant attention in the machine learning community due to their theoretical properties, such as…
Robust Graph Representation Learning via Predictive Coding
Billy Byiringiro, Tommaso Salvatori, Thomas Lukasiewicz
Predictive coding is a message-passing framework initially developed to model information processing in the brain, and now also topic of research in machine learning due to some in…
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…
Bird-Eye Transformers for Text Generation Models
Lei Sha, Yuhang Song, Yordan Yordanov +2
Transformers have become an indispensable module for text generation models since their great success in machine translation. Previous works attribute the~success of transformers t…