24 citations · 37 across the 7 of their papers we have counts for
7 papers
Wave propagation phenomena in nonlinear hierarchical neural networks with predictive coding feedback dynamics
Andrea Alamia, Léa Dalliès, Grégory Faye +1
We propose a mathematical framework to systematically explore the propagation properties of a class of continuous in time nonlinear neural network models comprising a hierarchy of…
Enhancing deep neural networks through complex-valued representations and Kuramoto synchronization dynamics
Sabine Muzellec, Andrea Alamia, Thomas Serre +1
Neural synchrony is hypothesized to play a crucial role in how the brain organizes visual scenes into structured representations, enabling the robust encoding of multiple objects w…
Understanding the computational demands underlying visual reasoning
Mohit Vaishnav, Remi Cadene, Andrea Alamia +3
Visual understanding requires comprehending complex visual relations between objects within a scene. Here, we seek to characterize the computational demands for abstract visual rea…
On the role of feedback in visual processing: a predictive coding perspective
Andrea Alamia, Milad Mozafari, Bhavin Choksi +1
Brain-inspired machine learning is gaining increasing consideration, particularly in computer vision. Several studies investigated the inclusion of top-down feedback connections in…
Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamics
Bhavin Choksi, Milad Mozafari, Callum Biggs O'May +3
Deep neural networks excel at image classification, but their performance is far less robust to input perturbations than human perception. In this work we explore whether this shor…
GAttANet: Global attention agreement for convolutional neural networks
Rufin VanRullen, Andrea Alamia
Transformer attention architectures, similar to those developed for natural language processing, have recently proved efficient also in vision, either in conjunction with or as a r…
Which Neural Network Architecture matches Human Behavior in Artificial Grammar Learning?
Andrea Alamia, Victor Gauducheau, Dimitri Paisios +1
In recent years artificial neural networks achieved performance close to or better than humans in several domains: tasks that were previously human prerogatives, such as language p…