17 citations · 92 across the 25 of their papers we have counts for
6 papers · 1 filter
Spontaneous Symmetry Breaking in Generative Diffusion Models
Gabriel Raya, Luca Ambrogioni
Generative diffusion models have recently emerged as a leading approach for generating high-dimensional data. In this paper, we show that the dynamics of these models exhibit a spo…
Gradient-adjusted Incremental Target Propagation Provides Effective Credit Assignment in Deep Neural Networks
Sander Dalm, Nasir Ahmad, Luca Ambrogioni +1
Many of the recent advances in the field of artificial intelligence have been fueled by the highly successful backpropagation of error (BP) algorithm, which efficiently solves the…
GAIT-prop: A biologically plausible learning rule derived from backpropagation of error
Nasir Ahmad, Marcel A. J. van Gerven, Luca Ambrogioni
Traditional backpropagation of error, though a highly successful algorithm for learning in artificial neural network models, includes features which are biologically implausible fo…
The Indian Chefs Process
Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier +6
This paper introduces the Indian Chefs Process (ICP), a Bayesian nonparametric prior on the joint space of infinite directed acyclic graphs (DAGs) and orders that generalizes India…
Background Hardly Matters: Understanding Personality Attribution in Deep Residual Networks
Gabriëlle Ras, Ron Dotsch, Luca Ambrogioni +2
Perceived personality traits attributed to an individual do not have to correspond to their actual personality traits and may be determined in part by the context in which one enco…
Temporal Factorization of 3D Convolutional Kernels
Gabriëlle Ras, Luca Ambrogioni, Umut Güçlü +1
3D convolutional neural networks are difficult to train because they are parameter-expensive and data-hungry. To solve these problems we propose a simple technique for learning 3D…