SSP 2023 Cover Page
2023
In the quest of using machines to predict and learn complex behaviors and situations, deep learning is the rage of the day.Recently, prediction rules based on so-called implicit models have emerged as a new high-potential paradigm in deep learning.These models rely on an "equilibrium" equation to define the prediction, instead of a recurrence through multiple layers.Currently, even very complex deep learning models are based on a "feedforward" structure, without loops, and as such the popular term "neural" applied to such models is not fully warranted, since the brain itself possesses loops.Allowing for loops may be a key to describe complex higher-level reasoning, which has so far eluded the deep learning paradigms.However, the new model raises the fundamental issue of well-posedness, since there may be no or multiple solutions to the corresponding equilibrium equation.