3 citations · 5 across the 8 of their papers we have counts for
4 papers · 1 filter
Avoidance of non-strict saddle points by blow-up
El Mehdi Achour, Umberto L. Hryniewicz, Michael Westdickenberg
It is an old idea to use gradient flows or time-discretized variants thereof as methods for solving minimization problems. In some applications, for example in machine learning con…
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…
The Riemannian Geometry Associated to Gradient Flows of Linear Convolutional Networks
El Mehdi Achour, Kathlén Kohn, Holger Rauhut
We study geometric properties of the gradient flow for learning deep linear convolutional networks. For linear fully connected networks, it has been shown recently that the corresp…
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…