Iteration seems to play a fundamental role in learning theory - as everywhere else. Since neurons need a rather long time to reach a stable state, Caianiello's Paradox suggests that special actions cause the iteration of state transitions until a stable neural state is reached. Now, a stable state is a fixed point for any transition function; so we may call the iteration above, we want to discuss, "fixed point iteration"
International audienceFixed-point iterations are commonly used to break the algebraic loops involved...
AbstractThe machine behaviour of a linear iteration is considered in the neighbourhood of a fixed po...
\u3cp\u3eIterative learning control (ILC) is an efficient way of improving the tracking performance ...
We present here lesson plans for teaching the dynamical systems topic of iteration of functions and ...
We study memory iteration where the updating consider a longer history of each site and the set of i...
Several learning algorithms have been derived for equilibrium points in recurrent neural networks. I...
The mechanisms underlying the dynamics of movement-related neural activity are not known. In this is...
In designing a neural net, either for biological modeling, cognitive simulation, or numerical comput...
<div>This presentation is about the theory of "Fixed Point Iteration Method" and its application. </...
The brain consists of many interconnected networks with time-varying, partially autonomous activity....
This paper empirically studies commonly observed training difficulties of Physics-Informed Neural Ne...
summary:Biological systems are able to switch their neural systems into inhibitory states and it is ...
All known structures involving a constructively obtainable fixed point (or it-eration) operation sat...
International audienceWe study the logical properties of the (parametric) well-founded fixed point o...
Abstract. Iteration exists extensively in the nature. Iteration of a homeo-morphism generates a dyna...
International audienceFixed-point iterations are commonly used to break the algebraic loops involved...
AbstractThe machine behaviour of a linear iteration is considered in the neighbourhood of a fixed po...
\u3cp\u3eIterative learning control (ILC) is an efficient way of improving the tracking performance ...
We present here lesson plans for teaching the dynamical systems topic of iteration of functions and ...
We study memory iteration where the updating consider a longer history of each site and the set of i...
Several learning algorithms have been derived for equilibrium points in recurrent neural networks. I...
The mechanisms underlying the dynamics of movement-related neural activity are not known. In this is...
In designing a neural net, either for biological modeling, cognitive simulation, or numerical comput...
<div>This presentation is about the theory of "Fixed Point Iteration Method" and its application. </...
The brain consists of many interconnected networks with time-varying, partially autonomous activity....
This paper empirically studies commonly observed training difficulties of Physics-Informed Neural Ne...
summary:Biological systems are able to switch their neural systems into inhibitory states and it is ...
All known structures involving a constructively obtainable fixed point (or it-eration) operation sat...
International audienceWe study the logical properties of the (parametric) well-founded fixed point o...
Abstract. Iteration exists extensively in the nature. Iteration of a homeo-morphism generates a dyna...
International audienceFixed-point iterations are commonly used to break the algebraic loops involved...
AbstractThe machine behaviour of a linear iteration is considered in the neighbourhood of a fixed po...
\u3cp\u3eIterative learning control (ILC) is an efficient way of improving the tracking performance ...